biGRU_attention.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\h5py\\__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\gensim\\utils.py:860: UserWarning: detected Windows; aliasing chunkize to chunkize_serial\n",
      "  warnings.warn(\"detected Windows; aliasing chunkize to chunkize_serial\")\n"
     ]
    }
   ],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import tensorflow as tf\n",
    "import keras\n",
    "# import gensim\n",
    "import numpy as np\n",
    "from tensorflow.examples.tutorials.mnist import input_data\n",
    "import os\n",
    "from os import listdir\n",
    "from os.path import isfile, join\n",
    "import random\n",
    "import shutil\n",
    "import pandas as pd\n",
    "from collections import defaultdict\n",
    "import re\n",
    "import gensim\n",
    "from bs4 import BeautifulSoup\n",
    "\n",
    "import sys\n",
    "from scipy import sparse\n",
    "\n",
    "from keras.preprocessing.text import Tokenizer, text_to_word_sequence\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "from keras.utils.np_utils import to_categorical\n",
    "import time\n",
    "\n",
    "from attention import * \n",
    "from tensorflow.python.ops.rnn import bidirectional_dynamic_rnn as bi_rnn\n",
    "from tensorflow.contrib.rnn import GRUCell\n",
    "\n",
    "from IPython.display import display, HTML\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "MAX_SENT_LENGTH = 100\n",
    "MAX_SENTS = 100 # this is the longest number of sentences in a document!!!\n",
    "MAX_NB_WORDS = 60000\n",
    "EMBEDDING_DIM = 300 #due to word2vec dimension!!! \n",
    "HIDDEN_SIZE = 50 #based on Yang et al CMU. (Hierachical Attention Networks for Document Classification)\n",
    "ATTENTION_SIZE = 100 #same as Yang et al. \n",
    "BATCH_SIZE = 50\n",
    "NUM_ITERS = 100\n",
    "DISPLAY_STEP = 10\n",
    "VALIDATION_STEP = 10\n",
    "TESTING_BATCH = 10\n",
    "USER_EMBEDDING_DIM = 200"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LOAD WORD VECTORS OF WORD2VEC MODEL \n",
    "src: https://github.com/mmihaltz/word2vec-GoogleNews-vectors/blob/master/GoogleNews-vectors-negative300.bin.gz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running time of loading Word2Vec model:  102.07301592826843\n"
     ]
    }
   ],
   "source": [
    "tic = time.time()\n",
    "word2vec = gensim.models.KeyedVectors.load_word2vec_format('GoogleNews-vectors-negative300.bin.gz', binary=True)\n",
    "toc = time.time()\n",
    "print(\"Running time of loading Word2Vec model: \", (toc - tic))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def batch_generator(X, y, batch_size):\n",
    "    \"\"\"Primitive batch generator \n",
    "    \"\"\"\n",
    "    size = X.shape[0]\n",
    "    X_copy = X.copy()\n",
    "    y_copy = y.copy()\n",
    "    indices = np.arange(size)\n",
    "    np.random.shuffle(indices)\n",
    "    X_copy = X_copy[indices]\n",
    "    y_copy = y_copy[indices]\n",
    "    i=0\n",
    "\n",
    "    while True:\n",
    "        left, right = i*batch_size, (i+1)*batch_size\n",
    "        right = min(size, right)\n",
    "        yield X_copy[left:right], y_copy[left:right]\n",
    "        if right >= size:\n",
    "            i = 0\n",
    "            indices = np.arange(size)\n",
    "            X_copy = X_copy[indices]\n",
    "            y_copy = y_copy[indices]\n",
    "        else:\n",
    "            i+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def fit_tokenizer_based_on_training(train_folder, test_folder, dict_selected_words,\n",
    "                                   ground_truth_file='snopes_ground_truth.csv'):\n",
    "    '''Return tensor data of URL based solely on training interactions only!!!'''\n",
    "    \n",
    "    \n",
    "    df = pd.read_csv(ground_truth_file)\n",
    "    full = zip(df['snopes_page'], df['claim_label'])\n",
    "    dict_url_ground_truth = {}\n",
    "    for url, label in full:\n",
    "        assert label == True or label == False\n",
    "        if label == True:\n",
    "            dict_url_ground_truth[url] = 1\n",
    "        elif label == False:\n",
    "            dict_url_ground_truth[url] = 0\n",
    "        \n",
    "    assert len(dict_url_ground_truth) == 562\n",
    "    \n",
    "    def read_text_files(infolder):\n",
    "        documents = [fn for fn in listdir(infolder) if fn.endswith('.txt')]\n",
    "        data = np.zeros((len(documents), MAX_SENTS, MAX_SENT_LENGTH), dtype='int32')\n",
    "        dict_docs = {}\n",
    "        for fn in documents:\n",
    "            p = join(infolder, fn)\n",
    "            fin1 = open(p, 'r')\n",
    "            url = fin1.readline().replace('\\n', '')\n",
    "            assert 'http' in url\n",
    "            sents = []\n",
    "            for line in fin1:\n",
    "                sents.append(line.replace('\\n', ''))\n",
    "            dict_docs[url] = sents\n",
    "                \n",
    "        Y = []\n",
    "        for idx, url in enumerate(dict_docs.keys()):\n",
    "            assert 'http' in url\n",
    "            label = dict_url_ground_truth[url]\n",
    "            assert label == 0 or label == 1\n",
    "            Y.append([label, 1-label])\n",
    "            sentences = dict_docs[url]\n",
    "            for j, sent in enumerate(sentences):\n",
    "                if j < MAX_SENTS:\n",
    "                    wordTokens = text_to_word_sequence(sent)\n",
    "                    k = 0\n",
    "                    for _, word in enumerate(wordTokens):\n",
    "                        if word not in dict_selected_words:\n",
    "                            continue\n",
    "                        index_of_word = dict_selected_words[word]\n",
    "                        assert index_of_word >= 1 and index_of_word <= 16000\n",
    "                        if k < MAX_SENT_LENGTH:\n",
    "                            data[idx, j, k] = index_of_word\n",
    "                            k+=1\n",
    "                    \n",
    "        return data, np.array(Y)\n",
    "        \n",
    "    X_train, y_train = read_text_files(infolder=train_folder)\n",
    "    X_test, y_test = read_text_files(infolder=test_folder)\n",
    "    print(y_train.shape, \"here\")\n",
    "    return X_train, y_train, X_test, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def load_url_content_text2num(selected_words_file='out_top_16K_words_file.txt'):\n",
    "    parent = \"train_test_data\"\n",
    "    dict_folds = {}\n",
    "    fin = open(selected_words_file, 'r')\n",
    "    cnt = 1\n",
    "    dict_selected_words = {}\n",
    "    for line in fin:\n",
    "        _, w, _ = line.split()\n",
    "        dict_selected_words[w] = cnt\n",
    "        cnt += 1\n",
    "    assert len(dict_selected_words) == 16000 and max(dict_selected_words.values()) == 16000\n",
    "    fin.close()\n",
    "    \n",
    "    for i in range(0, 5):\n",
    "        #########################################################\n",
    "        dict_words = {} #for stat\n",
    "        data_i = '%s/data_%s' % (parent, i)\n",
    "        train_folder = '%s/train' % data_i\n",
    "        test_folder = '%s/test' % data_i\n",
    "        X_train, y_train, X_test, y_test = fit_tokenizer_based_on_training(train_folder, test_folder, dict_selected_words)\n",
    "        dict_folds[i] = (X_train, y_train, X_test, y_test)\n",
    "        \n",
    "    return dict_folds, dict_selected_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(448, 2) here\n",
      "(448, 2) here\n",
      "(448, 2) here\n",
      "(448, 2) here\n",
      "(448, 2) here\n"
     ]
    }
   ],
   "source": [
    "dict_folds, dict_selected_words = load_url_content_text2num()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "no_vocabs = 16000 \n",
    "'''Word2vec embedding matrix'''\n",
    "embedding_matrix = np.random.random((no_vocabs, EMBEDDING_DIM))\n",
    "#i starts at 1 not 0 like normal stuff!!!!\n",
    "for word, i in dict_selected_words.items(): \n",
    "    if word in word2vec.wv.vocab:\n",
    "        embedding_vector = word2vec[word]\n",
    "        embedding_matrix[i-1] = embedding_vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def computeMetrics(true_labels, pred_labels):\n",
    "    assert y_true.shape == y_hat.shape\n",
    "    # True Positive (TP): we predict a label of 1 (positive), and the true label is 1.\n",
    "    TP = np.sum(np.logical_and(pred_labels == 1, true_labels == 1))  \n",
    "    # True Negative (TN): we predict a label of 0 (negative), and the true label is 0.\n",
    "    TN = np.sum(np.logical_and(pred_labels == 0, true_labels == 0))  \n",
    "    # False Positive (FP): we predict a label of 1 (positive), but the true label is 0.\n",
    "    FP = np.sum(np.logical_and(pred_labels == 1, true_labels == 0))  \n",
    "    # False Negative (FN): we predict a label of 0 (negative), but the true label is 1.\n",
    "    FN = np.sum(np.logical_and(pred_labels == 0, true_labels == 1))  \n",
    "    #print 'TP: %i, FP: %i, TN: %i, FN: %i' % (TP,FP,TN,FN)\n",
    "    assert TP+ TN+ FP+ FN == len(true_labels)\n",
    "    return TP, TN, FP, FN\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3, 5, 1, 1)\n"
     ]
    }
   ],
   "source": [
    "y_true = np.array([0,0, 1, 1, 1, 0, 0, 0, 1, 0]) \n",
    "y_hat = np.array([0, 0, 1, 1, 0, 1, 0, 0, 1, 0])\n",
    "print(computeMetrics(y_true, y_hat))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# BUILD BiGRU model + Attention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def buildModel():\n",
    "    tf.reset_default_graph() \n",
    "    '''Variable with shape (no_vocabs, EMBEDDING_DIM) to get vectors in a sentence'''\n",
    "    embedding_matrix_variable = tf.Variable(embedding_matrix, trainable=True, dtype=tf.float32)\n",
    "\n",
    "    '''We will take a bunch of sentences, where each sentence has length MAX_SENT_LENGTH\n",
    "    Ex: Two sentences: [[1,2,5,6,0], [3,5,3,6,0]] where numbers indicate a word. We will look up the \n",
    "    word vector for each word based on the number. \n",
    "    Hope it work. After looking up, the shape should be \n",
    "    (batch_size, MAX_SENTS, MAX_SENT_LENGTH, EMBEDDING_DIM)\n",
    "    However, since we need to use bi_rnn and we learn representation of sentences first. \n",
    "    Therefore, we should use shape \n",
    "    (?, MAX_SENT_LENGTH, EMBEDDING_DIM) where \"?\" should be a multiple of MAX_SENTS\n",
    "    '''\n",
    "    batch_sent_ph = tf.placeholder(tf.int32, [None, MAX_SENT_LENGTH], name=\"batch_sent_ph\")\n",
    "    batch_sent_embedded = tf.nn.embedding_lookup(embedding_matrix_variable, batch_sent_ph)\n",
    "    y_ph = tf.placeholder(tf.float32, [None, 2], name=\"labels\")\n",
    "    sentence_length_ph = tf.placeholder(tf.int32, [None], name=\"sentence_length_ph\")\n",
    "    doc_actual_length_ph = tf.placeholder(tf.int32, [None], name=\"doc_actual_length_ph\")\n",
    "    #print(batch_sent_embedded)\n",
    "\n",
    "    '''We do not specify sequence_length. \n",
    "    Therefore, the number of GRU cell in forward (same as backward) is MAX_SENT_LENGTH'''\n",
    "    with tf.variable_scope(\"first_bi_rnn\"):\n",
    "        rnn_outputs, _ = bi_rnn(GRUCell(HIDDEN_SIZE), GRUCell(HIDDEN_SIZE), \n",
    "                                inputs=batch_sent_embedded, \n",
    "                                sequence_length=sentence_length_ph, \n",
    "                                dtype=tf.float32)\n",
    "    with tf.name_scope(\"attention_first_bi_rnn\"):\n",
    "        attention_output, alphas_first = attention(rnn_outputs, ATTENTION_SIZE, return_alphas=True)\n",
    "    with tf.name_scope(\"dropout_afterfirst_bi_rnn\"):\n",
    "        dropout_first_bi_rnn = tf.nn.dropout(attention_output, keep_prob=0.8)\n",
    "    with tf.name_scope(\"sent_bedding_after_first_birnn\"):\n",
    "        sent_bedding_after_first_birnn = tf.reshape(dropout_first_bi_rnn, shape=[-1, MAX_SENTS, 2*HIDDEN_SIZE])\n",
    "    ###########second bi-rnn-layer ############################\n",
    "    with tf.variable_scope(\"second_bi_rnn\"):\n",
    "        bi_rnn_sent_outputs, _ = bi_rnn(GRUCell(2*HIDDEN_SIZE), GRUCell(2*HIDDEN_SIZE), \n",
    "                                        inputs=sent_bedding_after_first_birnn, \n",
    "                                        sequence_length=doc_actual_length_ph,\n",
    "                                        dtype=tf.float32)\n",
    "    with tf.name_scope(\"attention_second_bi_rnn\"):\n",
    "        attention_output2, alphas_second = attention(bi_rnn_sent_outputs, ATTENTION_SIZE, return_alphas=True)\n",
    "    with tf.name_scope(\"dropout_after_second_bi_rnn\"):\n",
    "        dropout_second_bi_rnn = tf.nn.dropout(attention_output2, keep_prob=0.8)\n",
    "\n",
    "    with tf.name_scope(\"FC_layer\"):\n",
    "        W = tf.Variable(tf.random_normal([HIDDEN_SIZE * 4, 2], stddev=0.1))\n",
    "        b = tf.Variable(tf.constant(0.1, shape=[1]))\n",
    "        y_hat = tf.matmul(dropout_second_bi_rnn, W) + b\n",
    "    #y_hat = tf.squeeze(y_hat)\n",
    "\n",
    "    with tf.name_scope(\"softmax\"):\n",
    "        out_softmax = tf.nn.softmax(logits=y_hat)\n",
    "\n",
    "    with tf.name_scope(\"loss_cross_entropy\"):\n",
    "        loss = -tf.reduce_mean(tf.reduce_sum(tf.cast(y_ph, tf.float32) * tf.log(out_softmax), axis=1))\n",
    "    #loss = tf.reduce_sum(out_softmax)\n",
    "    A = tf.summary.scalar(\"Loss\", loss)\n",
    "\n",
    "    with tf.variable_scope(\"Traininig\"):\n",
    "        train_step = tf.train.AdamOptimizer(1e-4).minimize(loss=loss)\n",
    "\n",
    "    with tf.variable_scope(\"evaluation\"):\n",
    "        ground_truth = tf.argmax(y_ph, 1)\n",
    "        predicted = tf.argmax(out_softmax, 1)\n",
    "        correct_prediction = tf.equal(predicted, ground_truth)\n",
    "        accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n",
    "        accuracy_test = tf.reduce_sum(tf.cast(correct_prediction, tf.float32))\n",
    "\n",
    "    valVar = tf.Variable(0.0, \"valVar\")\n",
    "    valVal_ph = tf.placeholder(tf.float32, [], name=\"independent\")\n",
    "    update_valVar = valVar.assign(valVal_ph)\n",
    "    mySummary = tf.summary.scalar(\"Validation\", update_valVar)\n",
    "\n",
    "    B = tf.summary.scalar(\"Accuracy\", accuracy)\n",
    "    summary_op = tf.summary.merge([A, B])\n",
    "    placeholder_input = (batch_sent_ph, y_ph, sentence_length_ph, doc_actual_length_ph, valVal_ph)\n",
    "    components = [accuracy, accuracy_test, update_valVar, mySummary, \n",
    "                  summary_op, train_step, ground_truth, predicted, alphas_first, alphas_second]\n",
    "    return  components, placeholder_input"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fitting model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def fit(X_train, y_train, X_test, y_test, log_dir, outfile):\n",
    "\n",
    "    train_batch_generator = batch_generator(X_train, y_train, BATCH_SIZE)\n",
    "    components, placeholder_input = buildModel()\n",
    "    batch_sent_ph, y_ph, sentence_length_ph, doc_actual_length_ph, valVal_ph = placeholder_input\n",
    "    accuracy, accuracy_test, update_valVar, mySummary, summary_op, train_step, ground_truth, predicted, _, _ = components\n",
    "    fout = open(outfile, 'w')\n",
    "    pre_val_acc = -1\n",
    "    best_results = None\n",
    "    time_val_acc_reduced = 0\n",
    "    STOP_TRAINING = False\n",
    "    saver = tf.train.Saver()\n",
    "\n",
    "    with tf.Session() as sess:\n",
    "        sess.run(tf.global_variables_initializer())\n",
    "        sess.run(tf.local_variables_initializer())\n",
    "\n",
    "\n",
    "        writer = tf.summary.FileWriter(log_dir, graph=sess.graph)\n",
    "        cnt_step = 0\n",
    "        for i in range(NUM_ITERS):\n",
    "            num_batches = X_train.shape[0] / float(BATCH_SIZE)\n",
    "            num_batches = int(num_batches)\n",
    "\n",
    "            for b in range(num_batches):\n",
    "                x_batch, y_batch = next(train_batch_generator)\n",
    "                temp = np.sum(x_batch, axis=2)\n",
    "                doc_actual_lengths_better = np.count_nonzero(temp, axis=1) \n",
    "\n",
    "                #when reshaping data for feeddict, you should use np.reshape\n",
    "                x_batch = x_batch.reshape(-1, MAX_SENT_LENGTH)\n",
    "                '''Actual length of sentences in this batch_size * so_luong_sentence_moi_doc'''\n",
    "                sentence_actual_lengths_better = np.count_nonzero(x_batch, axis=1)\n",
    "                if cnt_step % DISPLAY_STEP == 0:\n",
    "                    #print(\"At iter %s and batch %s of %s - cntStep: %s\" % (i, b, num_batches, cnt_step))\n",
    "                    train_acc = accuracy.eval(feed_dict={batch_sent_ph: x_batch, y_ph: y_batch,\n",
    "                                                       sentence_length_ph: sentence_actual_lengths_better,\n",
    "                                                       doc_actual_length_ph: doc_actual_lengths_better\n",
    "                                                       })\n",
    "                    print(\"Training accuracy at [iter %s][batch %s of %s][cntStep: %s] : %s\" % \n",
    "                          (i, b, num_batches, cnt_step, train_acc))\n",
    "                    fout.write('%s\\n' % \"Training accuracy at [iter %s][batch %s of %s][cntStep: %s] : %s\" % \n",
    "                          (i, b, num_batches, cnt_step, train_acc))\n",
    "                    fout.flush()\n",
    "                ########################################################\n",
    "                ### VALIDATION STEP ####################################\n",
    "                ########################################################\n",
    "                if cnt_step % VALIDATION_STEP == 0:\n",
    "                    #do validation\n",
    "                    curr_val_acc, curr_fp, curr_fn = doValidation(X_data=X_test, y_data=y_test, curr_sess=sess,\n",
    "                                 metrics=[accuracy_test, ground_truth, predicted], \n",
    "                                                batch_size=TESTING_BATCH, prefix=\"Validation\",\n",
    "                                placeholder_input=placeholder_input)\n",
    "                    print(('Validation accuracy is: %s, fp:%s, fn:%s on shape %s' % \n",
    "                                         (curr_val_acc, curr_fp, curr_fn, str(X_test.shape))))\n",
    "                    fout.write('%s\\n' % ('Validation accuracy is: %s, fp:%s, fn:%s on shape %s' % \n",
    "                                         (curr_val_acc, curr_fp, curr_fn, str(X_test.shape))))\n",
    "                    fout.flush()\n",
    "                    _, ss = sess.run([update_valVar, mySummary], feed_dict={valVal_ph: curr_val_acc})\n",
    "                    writer.add_summary(ss, cnt_step)\n",
    "\n",
    "                    if curr_val_acc >= pre_val_acc:\n",
    "                        pre_val_acc = curr_val_acc\n",
    "                        time_val_acc_reduced = 0\n",
    "                        best_results = [curr_val_acc, curr_fp, curr_fn]\n",
    "                        saver.save(sess, 'saved_models/bestBiGRU_attention_%s' % outfile)\n",
    "\n",
    "\n",
    "                #assert x_batch.shape == (BATCH_SIZE * MAX_SENTS, MAX_SENT_LENGTH), x_batch.shape\n",
    "                summary, _ = sess.run([summary_op, train_step], \n",
    "                                             feed_dict={batch_sent_ph: x_batch, y_ph: y_batch,\n",
    "                                                       sentence_length_ph: sentence_actual_lengths_better,\n",
    "                                                       doc_actual_length_ph: doc_actual_lengths_better\n",
    "                                                       })\n",
    "                writer.add_summary(summary, cnt_step)\n",
    "                cnt_step += 1\n",
    "\n",
    "        writer.close()\n",
    "        #testing data\n",
    "        best_testing_acc = pre_val_acc\n",
    "        print('Best Testing accuracy is: ', best_testing_acc, ' on shape ', X_test.shape)\n",
    "        fout.write('%s\\n' % ('Best Testing ACC: %s, FP:%s, FN:%s on shape %s' % (best_results[0], best_results[1], \n",
    "                                                                                 best_results[2], str(X_test.shape))))\n",
    "        fout.flush()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def doValidation(X_data, y_data, curr_sess, metrics, batch_size, prefix, placeholder_input):\n",
    "    accuracy, ground_truth, predicted = metrics\n",
    "    num_batches = X_data.shape[0] / float(batch_size)\n",
    "    num_batches = int(num_batches)\n",
    "    sum_acc, sum_fp, sum_fn, sum_TP, sum_TN = 0, 0, 0, 0, 0\n",
    "    cnt_rows = 0\n",
    "    batch_sent_ph, y_ph, sentence_length_ph, doc_actual_length_ph, _ = placeholder_input\n",
    "    test_batch_generator = batch_generator(X_data, y_data, batch_size)\n",
    "    for i in range(num_batches+1):\n",
    "\n",
    "        x_batch, y_batch = next(test_batch_generator)\n",
    "        temp = np.sum(x_batch, axis=2)\n",
    "        #print(\"Test data shape: \", x_batch.shape)\n",
    "        doc_actual_lengths_test = np.count_nonzero(temp, axis=1) \n",
    "        x_batch_reshaped = x_batch.reshape(-1, MAX_SENT_LENGTH)\n",
    "        sentence_actual_lengths_test = np.count_nonzero(x_batch_reshaped, axis=1)\n",
    "        acc_result, true_labels, pred_labels = curr_sess.run([accuracy, ground_truth, predicted], \n",
    "                                                   feed_dict={batch_sent_ph: x_batch_reshaped, \n",
    "                                    y_ph: y_batch, sentence_length_ph: sentence_actual_lengths_test,\n",
    "                                    doc_actual_length_ph: doc_actual_lengths_test})\n",
    "\n",
    "        tp_res, tn_res, fp_res, fn_res = computeMetrics(true_labels=true_labels, pred_labels=pred_labels)\n",
    "\n",
    "        assert abs(fp_res+tn_res+tp_res+fn_res - x_batch.shape[0]) < 1e-10, 'fp: %s, tn: %s, tp: %s, fn:%s vs. %s' % (fp_res, tn_res, tp_res, fn_res, x_batch.shape[0])\n",
    "        sum_acc += acc_result\n",
    "        sum_fp += fp_res\n",
    "        sum_fn += fn_res\n",
    "        sum_TP += tp_res\n",
    "        sum_TN += tn_res\n",
    "        #sum_fp += (fp_res/float(fp_res+tn_res))\n",
    "        #sum_fn += fn_res/float(tp_res+fn_res)\n",
    "        cnt_rows += x_batch.shape[0]\n",
    "    assert cnt_rows == X_data.shape[0], 'Mismatched rows_count: %s vs. %s' % (cnt_rows, X_data.shape[0])\n",
    "    rr = sum_acc/float(X_data.shape[0])\n",
    "    rr_fp = sum_fp/float(sum_fp+ sum_TN)\n",
    "    rr_fn = sum_fn/float(sum_TP+ sum_fn)\n",
    "    return rr, rr_fp, rr_fn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def train_BiGRU():\n",
    "    log_dir = \"HAM_log\"\n",
    "    for key in dict_folds:\n",
    "        X_train, y_train, X_test, y_test = dict_folds[key]\n",
    "        #clear log_dir\n",
    "        if os.path.exists(log_dir):\n",
    "            shutil.rmtree(log_dir)\n",
    "\n",
    "        fit(X_train, y_train, X_test, y_test, log_dir, outfile='log_result_%s' % (key))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training the Bi-Directional GRU with Word Attention and Stentence Attention"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training accuracy at [iter 0][batch 0 of 8][cntStep: 0] : 0.42\n",
      "Validation accuracy is: 0.526315789474, fp:0.771929824561, fn:0.175438596491 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 1][batch 2 of 8][cntStep: 10] : 0.36\n",
      "Validation accuracy is: 0.526315789474, fp:0.315789473684, fn:0.631578947368 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 2][batch 4 of 8][cntStep: 20] : 0.54\n",
      "Validation accuracy is: 0.543859649123, fp:0.0175438596491, fn:0.894736842105 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 3][batch 6 of 8][cntStep: 30] : 0.44\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 5][batch 0 of 8][cntStep: 40] : 0.5\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 6][batch 2 of 8][cntStep: 50] : 0.56\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 7][batch 4 of 8][cntStep: 60] : 0.58\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 8][batch 6 of 8][cntStep: 70] : 0.6\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 10][batch 0 of 8][cntStep: 80] : 0.375\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 11][batch 2 of 8][cntStep: 90] : 0.54\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 12][batch 4 of 8][cntStep: 100] : 0.34\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 13][batch 6 of 8][cntStep: 110] : 0.58\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 15][batch 0 of 8][cntStep: 120] : 0.42\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 16][batch 2 of 8][cntStep: 130] : 0.5\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 17][batch 4 of 8][cntStep: 140] : 0.58\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 18][batch 6 of 8][cntStep: 150] : 0.64\n",
      "Validation accuracy is: 0.526315789474, fp:0.0350877192982, fn:0.912280701754 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 20][batch 0 of 8][cntStep: 160] : 0.62\n",
      "Validation accuracy is: 0.552631578947, fp:0.0175438596491, fn:0.877192982456 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 21][batch 2 of 8][cntStep: 170] : 0.520833\n",
      "Validation accuracy is: 0.543859649123, fp:0.0701754385965, fn:0.842105263158 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 22][batch 4 of 8][cntStep: 180] : 0.74\n",
      "Validation accuracy is: 0.570175438596, fp:0.0175438596491, fn:0.842105263158 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 23][batch 6 of 8][cntStep: 190] : 0.72\n",
      "Validation accuracy is: 0.614035087719, fp:0.0526315789474, fn:0.719298245614 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 25][batch 0 of 8][cntStep: 200] : 0.88\n",
      "Validation accuracy is: 0.631578947368, fp:0.0877192982456, fn:0.649122807018 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 26][batch 2 of 8][cntStep: 210] : 0.88\n",
      "Validation accuracy is: 0.675438596491, fp:0.0526315789474, fn:0.59649122807 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 27][batch 4 of 8][cntStep: 220] : 0.92\n",
      "Validation accuracy is: 0.657894736842, fp:0.0877192982456, fn:0.59649122807 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 28][batch 6 of 8][cntStep: 230] : 0.92\n",
      "Validation accuracy is: 0.666666666667, fp:0.561403508772, fn:0.105263157895 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 30][batch 0 of 8][cntStep: 240] : 1.0\n",
      "Validation accuracy is: 0.728070175439, fp:0.280701754386, fn:0.263157894737 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 31][batch 2 of 8][cntStep: 250] : 0.96\n",
      "Validation accuracy is: 0.701754385965, fp:0.368421052632, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 32][batch 4 of 8][cntStep: 260] : 0.979167\n",
      "Validation accuracy is: 0.710526315789, fp:0.333333333333, fn:0.245614035088 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 33][batch 6 of 8][cntStep: 270] : 1.0\n",
      "Validation accuracy is: 0.69298245614, fp:0.298245614035, fn:0.315789473684 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 35][batch 0 of 8][cntStep: 280] : 0.98\n",
      "Validation accuracy is: 0.69298245614, fp:0.19298245614, fn:0.421052631579 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 36][batch 2 of 8][cntStep: 290] : 0.96\n",
      "Validation accuracy is: 0.719298245614, fp:0.333333333333, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 37][batch 4 of 8][cntStep: 300] : 1.0\n",
      "Validation accuracy is: 0.780701754386, fp:0.210526315789, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 38][batch 6 of 8][cntStep: 310] : 1.0\n",
      "Validation accuracy is: 0.745614035088, fp:0.228070175439, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 40][batch 0 of 8][cntStep: 320] : 1.0\n",
      "Validation accuracy is: 0.745614035088, fp:0.245614035088, fn:0.263157894737 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 41][batch 2 of 8][cntStep: 330] : 1.0\n",
      "Validation accuracy is: 0.815789473684, fp:0.19298245614, fn:0.175438596491 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 42][batch 4 of 8][cntStep: 340] : 1.0\n",
      "Validation accuracy is: 0.736842105263, fp:0.298245614035, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 43][batch 6 of 8][cntStep: 350] : 1.0\n",
      "Validation accuracy is: 0.745614035088, fp:0.228070175439, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 45][batch 0 of 8][cntStep: 360] : 1.0\n",
      "Validation accuracy is: 0.745614035088, fp:0.245614035088, fn:0.263157894737 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 46][batch 2 of 8][cntStep: 370] : 0.98\n",
      "Validation accuracy is: 0.736842105263, fp:0.298245614035, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 47][batch 4 of 8][cntStep: 380] : 1.0\n",
      "Validation accuracy is: 0.736842105263, fp:0.350877192982, fn:0.175438596491 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 48][batch 6 of 8][cntStep: 390] : 1.0\n",
      "Validation accuracy is: 0.763157894737, fp:0.245614035088, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Best Testing accuracy is:  0.815789473684  on shape  (114, 100, 100)\n",
      "Training accuracy at [iter 0][batch 0 of 8][cntStep: 0] : 0.46\n",
      "Validation accuracy is: 0.508771929825, fp:0.350877192982, fn:0.631578947368 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 1][batch 2 of 8][cntStep: 10] : 0.6\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 2][batch 4 of 8][cntStep: 20] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 3][batch 6 of 8][cntStep: 30] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 5][batch 0 of 8][cntStep: 40] : 0.36\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 6][batch 2 of 8][cntStep: 50] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 7][batch 4 of 8][cntStep: 60] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 8][batch 6 of 8][cntStep: 70] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 10][batch 0 of 8][cntStep: 80] : 0.5625\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 11][batch 2 of 8][cntStep: 90] : 0.5\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 12][batch 4 of 8][cntStep: 100] : 0.6\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 13][batch 6 of 8][cntStep: 110] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 15][batch 0 of 8][cntStep: 120] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 16][batch 2 of 8][cntStep: 130] : 0.36\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 17][batch 4 of 8][cntStep: 140] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 18][batch 6 of 8][cntStep: 150] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 20][batch 0 of 8][cntStep: 160] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 21][batch 2 of 8][cntStep: 170] : 0.583333\n",
      "Validation accuracy is: 0.517543859649, fp:0.0, fn:0.964912280702 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 22][batch 4 of 8][cntStep: 180] : 0.6\n",
      "Validation accuracy is: 0.508771929825, fp:0.0175438596491, fn:0.964912280702 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 23][batch 6 of 8][cntStep: 190] : 0.96\n",
      "Validation accuracy is: 0.570175438596, fp:0.0175438596491, fn:0.842105263158 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 25][batch 0 of 8][cntStep: 200] : 0.92\n",
      "Validation accuracy is: 0.631578947368, fp:0.0701754385965, fn:0.666666666667 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 26][batch 2 of 8][cntStep: 210] : 0.88\n",
      "Validation accuracy is: 0.552631578947, fp:0.0350877192982, fn:0.859649122807 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 27][batch 4 of 8][cntStep: 220] : 0.92\n",
      "Validation accuracy is: 0.552631578947, fp:0.0526315789474, fn:0.842105263158 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 28][batch 6 of 8][cntStep: 230] : 1.0\n",
      "Validation accuracy is: 0.631578947368, fp:0.385964912281, fn:0.350877192982 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 30][batch 0 of 8][cntStep: 240] : 0.98\n",
      "Validation accuracy is: 0.622807017544, fp:0.298245614035, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 31][batch 2 of 8][cntStep: 250] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.315789473684, fn:0.438596491228 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 32][batch 4 of 8][cntStep: 260] : 1.0\n",
      "Validation accuracy is: 0.649122807018, fp:0.40350877193, fn:0.298245614035 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 33][batch 6 of 8][cntStep: 270] : 1.0\n",
      "Validation accuracy is: 0.587719298246, fp:0.438596491228, fn:0.385964912281 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 35][batch 0 of 8][cntStep: 280] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.245614035088, fn:0.473684210526 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 36][batch 2 of 8][cntStep: 290] : 1.0\n",
      "Validation accuracy is: 0.631578947368, fp:0.263157894737, fn:0.473684210526 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 37][batch 4 of 8][cntStep: 300] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.333333333333, fn:0.385964912281 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 38][batch 6 of 8][cntStep: 310] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.315789473684, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 40][batch 0 of 8][cntStep: 320] : 0.98\n",
      "Validation accuracy is: 0.640350877193, fp:0.315789473684, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 41][batch 2 of 8][cntStep: 330] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.298245614035, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 42][batch 4 of 8][cntStep: 340] : 1.0\n",
      "Validation accuracy is: 0.614035087719, fp:0.315789473684, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 43][batch 6 of 8][cntStep: 350] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.280701754386, fn:0.438596491228 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 45][batch 0 of 8][cntStep: 360] : 1.0\n",
      "Validation accuracy is: 0.59649122807, fp:0.350877192982, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 46][batch 2 of 8][cntStep: 370] : 1.0\n",
      "Validation accuracy is: 0.614035087719, fp:0.315789473684, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 47][batch 4 of 8][cntStep: 380] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.280701754386, fn:0.438596491228 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 48][batch 6 of 8][cntStep: 390] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.333333333333, fn:0.421052631579 on shape (114, 100, 100)\n",
      "Best Testing accuracy is:  0.649122807018  on shape  (114, 100, 100)\n",
      "Training accuracy at [iter 0][batch 0 of 8][cntStep: 0] : 0.62\n",
      "Validation accuracy is: 0.508771929825, fp:0.0175438596491, fn:0.964912280702 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 1][batch 2 of 8][cntStep: 10] : 0.4\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 2][batch 4 of 8][cntStep: 20] : 0.54\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 3][batch 6 of 8][cntStep: 30] : 0.58\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 5][batch 0 of 8][cntStep: 40] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 6][batch 2 of 8][cntStep: 50] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 7][batch 4 of 8][cntStep: 60] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 8][batch 6 of 8][cntStep: 70] : 0.32\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 10][batch 0 of 8][cntStep: 80] : 0.5625\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 11][batch 2 of 8][cntStep: 90] : 0.62\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 12][batch 4 of 8][cntStep: 100] : 0.4\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 13][batch 6 of 8][cntStep: 110] : 0.54\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 15][batch 0 of 8][cntStep: 120] : 0.58\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 16][batch 2 of 8][cntStep: 130] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 17][batch 4 of 8][cntStep: 140] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 18][batch 6 of 8][cntStep: 150] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 20][batch 0 of 8][cntStep: 160] : 0.32\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 21][batch 2 of 8][cntStep: 170] : 0.5625\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 22][batch 4 of 8][cntStep: 180] : 0.64\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 23][batch 6 of 8][cntStep: 190] : 0.56\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 25][batch 0 of 8][cntStep: 200] : 0.7\n",
      "Validation accuracy is: 0.526315789474, fp:0.0, fn:0.947368421053 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 26][batch 2 of 8][cntStep: 210] : 0.86\n",
      "Validation accuracy is: 0.587719298246, fp:0.0, fn:0.824561403509 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 27][batch 4 of 8][cntStep: 220] : 0.9\n",
      "Validation accuracy is: 0.587719298246, fp:0.0526315789474, fn:0.771929824561 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 28][batch 6 of 8][cntStep: 230] : 0.92\n",
      "Validation accuracy is: 0.59649122807, fp:0.0701754385965, fn:0.736842105263 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 30][batch 0 of 8][cntStep: 240] : 0.98\n",
      "Validation accuracy is: 0.614035087719, fp:0.105263157895, fn:0.666666666667 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 31][batch 2 of 8][cntStep: 250] : 0.92\n",
      "Validation accuracy is: 0.657894736842, fp:0.122807017544, fn:0.561403508772 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 32][batch 4 of 8][cntStep: 260] : 0.979167\n",
      "Validation accuracy is: 0.622807017544, fp:0.350877192982, fn:0.40350877193 on shape (114, 100, 100)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training accuracy at [iter 33][batch 6 of 8][cntStep: 270] : 0.96\n",
      "Validation accuracy is: 0.649122807018, fp:0.245614035088, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 35][batch 0 of 8][cntStep: 280] : 0.98\n",
      "Validation accuracy is: 0.605263157895, fp:0.736842105263, fn:0.0526315789474 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 36][batch 2 of 8][cntStep: 290] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.245614035088, fn:0.508771929825 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 37][batch 4 of 8][cntStep: 300] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.578947368421, fn:0.140350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 38][batch 6 of 8][cntStep: 310] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.666666666667, fn:0.0877192982456 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 40][batch 0 of 8][cntStep: 320] : 1.0\n",
      "Validation accuracy is: 0.631578947368, fp:0.473684210526, fn:0.263157894737 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 41][batch 2 of 8][cntStep: 330] : 0.98\n",
      "Validation accuracy is: 0.631578947368, fp:0.385964912281, fn:0.350877192982 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 42][batch 4 of 8][cntStep: 340] : 1.0\n",
      "Validation accuracy is: 0.631578947368, fp:0.385964912281, fn:0.350877192982 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 43][batch 6 of 8][cntStep: 350] : 1.0\n",
      "Validation accuracy is: 0.666666666667, fp:0.40350877193, fn:0.263157894737 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 45][batch 0 of 8][cntStep: 360] : 1.0\n",
      "Validation accuracy is: 0.657894736842, fp:0.40350877193, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 46][batch 2 of 8][cntStep: 370] : 1.0\n",
      "Validation accuracy is: 0.69298245614, fp:0.385964912281, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 47][batch 4 of 8][cntStep: 380] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.385964912281, fn:0.333333333333 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 48][batch 6 of 8][cntStep: 390] : 1.0\n",
      "Validation accuracy is: 0.649122807018, fp:0.421052631579, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Best Testing accuracy is:  0.69298245614  on shape  (114, 100, 100)\n",
      "Training accuracy at [iter 0][batch 0 of 8][cntStep: 0] : 0.58\n",
      "Validation accuracy is: 0.517543859649, fp:0.228070175439, fn:0.736842105263 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 1][batch 2 of 8][cntStep: 10] : 0.62\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 2][batch 4 of 8][cntStep: 20] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 3][batch 6 of 8][cntStep: 30] : 0.56\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 5][batch 0 of 8][cntStep: 40] : 0.54\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 6][batch 2 of 8][cntStep: 50] : 0.44\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 7][batch 4 of 8][cntStep: 60] : 0.42\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 8][batch 6 of 8][cntStep: 70] : 0.42\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 10][batch 0 of 8][cntStep: 80] : 0.541667\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 11][batch 2 of 8][cntStep: 90] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 12][batch 4 of 8][cntStep: 100] : 0.62\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 13][batch 6 of 8][cntStep: 110] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 15][batch 0 of 8][cntStep: 120] : 0.56\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 16][batch 2 of 8][cntStep: 130] : 0.54\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 17][batch 4 of 8][cntStep: 140] : 0.44\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 18][batch 6 of 8][cntStep: 150] : 0.42\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 20][batch 0 of 8][cntStep: 160] : 0.44\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 21][batch 2 of 8][cntStep: 170] : 0.541667\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 22][batch 4 of 8][cntStep: 180] : 0.5\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 23][batch 6 of 8][cntStep: 190] : 0.76\n",
      "Validation accuracy is: 0.543859649123, fp:0.0, fn:0.912280701754 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 25][batch 0 of 8][cntStep: 200] : 0.84\n",
      "Validation accuracy is: 0.552631578947, fp:0.0, fn:0.894736842105 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 26][batch 2 of 8][cntStep: 210] : 0.88\n",
      "Validation accuracy is: 0.561403508772, fp:0.0526315789474, fn:0.824561403509 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 27][batch 4 of 8][cntStep: 220] : 0.94\n",
      "Validation accuracy is: 0.552631578947, fp:0.0526315789474, fn:0.842105263158 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 28][batch 6 of 8][cntStep: 230] : 0.9\n",
      "Validation accuracy is: 0.561403508772, fp:0.0701754385965, fn:0.80701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 30][batch 0 of 8][cntStep: 240] : 0.98\n",
      "Validation accuracy is: 0.614035087719, fp:0.0877192982456, fn:0.684210526316 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 31][batch 2 of 8][cntStep: 250] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.157894736842, fn:0.561403508772 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 32][batch 4 of 8][cntStep: 260] : 0.979167\n",
      "Validation accuracy is: 0.622807017544, fp:0.19298245614, fn:0.561403508772 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 33][batch 6 of 8][cntStep: 270] : 1.0\n",
      "Validation accuracy is: 0.675438596491, fp:0.245614035088, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 35][batch 0 of 8][cntStep: 280] : 0.98\n",
      "Validation accuracy is: 0.614035087719, fp:0.263157894737, fn:0.508771929825 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 36][batch 2 of 8][cntStep: 290] : 0.98\n",
      "Validation accuracy is: 0.631578947368, fp:0.508771929825, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 37][batch 4 of 8][cntStep: 300] : 1.0\n",
      "Validation accuracy is: 0.622807017544, fp:0.315789473684, fn:0.438596491228 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 38][batch 6 of 8][cntStep: 310] : 1.0\n",
      "Validation accuracy is: 0.640350877193, fp:0.438596491228, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 40][batch 0 of 8][cntStep: 320] : 1.0\n",
      "Validation accuracy is: 0.675438596491, fp:0.19298245614, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 41][batch 2 of 8][cntStep: 330] : 1.0\n",
      "Validation accuracy is: 0.657894736842, fp:0.210526315789, fn:0.473684210526 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 42][batch 4 of 8][cntStep: 340] : 1.0\n",
      "Validation accuracy is: 0.666666666667, fp:0.245614035088, fn:0.421052631579 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 43][batch 6 of 8][cntStep: 350] : 1.0\n",
      "Validation accuracy is: 0.657894736842, fp:0.280701754386, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 45][batch 0 of 8][cntStep: 360] : 1.0\n",
      "Validation accuracy is: 0.666666666667, fp:0.298245614035, fn:0.368421052632 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 46][batch 2 of 8][cntStep: 370] : 1.0\n",
      "Validation accuracy is: 0.657894736842, fp:0.263157894737, fn:0.421052631579 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 47][batch 4 of 8][cntStep: 380] : 1.0\n",
      "Validation accuracy is: 0.631578947368, fp:0.368421052632, fn:0.368421052632 on shape (114, 100, 100)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training accuracy at [iter 48][batch 6 of 8][cntStep: 390] : 1.0\n",
      "Validation accuracy is: 0.684210526316, fp:0.245614035088, fn:0.385964912281 on shape (114, 100, 100)\n",
      "Best Testing accuracy is:  0.684210526316  on shape  (114, 100, 100)\n",
      "Training accuracy at [iter 0][batch 0 of 8][cntStep: 0] : 0.5\n",
      "Validation accuracy is: 0.491228070175, fp:1.0, fn:0.0175438596491 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 1][batch 2 of 8][cntStep: 10] : 0.56\n",
      "Validation accuracy is: 0.587719298246, fp:0.508771929825, fn:0.315789473684 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 2][batch 4 of 8][cntStep: 20] : 0.52\n",
      "Validation accuracy is: 0.517543859649, fp:0.0, fn:0.964912280702 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 3][batch 6 of 8][cntStep: 30] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 5][batch 0 of 8][cntStep: 40] : 0.62\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 6][batch 2 of 8][cntStep: 50] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 7][batch 4 of 8][cntStep: 60] : 0.52\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 8][batch 6 of 8][cntStep: 70] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 10][batch 0 of 8][cntStep: 80] : 0.479167\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 11][batch 2 of 8][cntStep: 90] : 0.5\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 12][batch 4 of 8][cntStep: 100] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 13][batch 6 of 8][cntStep: 110] : 0.48\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 15][batch 0 of 8][cntStep: 120] : 0.46\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 16][batch 2 of 8][cntStep: 130] : 0.62\n",
      "Validation accuracy is: 0.5, fp:0.0, fn:1.0 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 17][batch 4 of 8][cntStep: 140] : 0.48\n",
      "Validation accuracy is: 0.508771929825, fp:0.0, fn:0.982456140351 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 18][batch 6 of 8][cntStep: 150] : 0.52\n",
      "Validation accuracy is: 0.517543859649, fp:0.0, fn:0.964912280702 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 20][batch 0 of 8][cntStep: 160] : 0.58\n",
      "Validation accuracy is: 0.526315789474, fp:0.0, fn:0.947368421053 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 21][batch 2 of 8][cntStep: 170] : 0.604167\n",
      "Validation accuracy is: 0.543859649123, fp:0.0, fn:0.912280701754 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 22][batch 4 of 8][cntStep: 180] : 0.84\n",
      "Validation accuracy is: 0.587719298246, fp:0.0350877192982, fn:0.789473684211 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 23][batch 6 of 8][cntStep: 190] : 0.92\n",
      "Validation accuracy is: 0.69298245614, fp:0.105263157895, fn:0.508771929825 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 25][batch 0 of 8][cntStep: 200] : 0.72\n",
      "Validation accuracy is: 0.59649122807, fp:0.0, fn:0.80701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 26][batch 2 of 8][cntStep: 210] : 0.86\n",
      "Validation accuracy is: 0.614035087719, fp:0.0701754385965, fn:0.701754385965 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 27][batch 4 of 8][cntStep: 220] : 0.86\n",
      "Validation accuracy is: 0.605263157895, fp:0.0175438596491, fn:0.771929824561 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 28][batch 6 of 8][cntStep: 230] : 0.94\n",
      "Validation accuracy is: 0.605263157895, fp:0.122807017544, fn:0.666666666667 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 30][batch 0 of 8][cntStep: 240] : 0.94\n",
      "Validation accuracy is: 0.587719298246, fp:0.0877192982456, fn:0.736842105263 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 31][batch 2 of 8][cntStep: 250] : 0.98\n",
      "Validation accuracy is: 0.649122807018, fp:0.228070175439, fn:0.473684210526 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 32][batch 4 of 8][cntStep: 260] : 0.875\n",
      "Validation accuracy is: 0.578947368421, fp:0.736842105263, fn:0.105263157895 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 33][batch 6 of 8][cntStep: 270] : 0.9\n",
      "Validation accuracy is: 0.59649122807, fp:0.140350877193, fn:0.666666666667 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 35][batch 0 of 8][cntStep: 280] : 0.98\n",
      "Validation accuracy is: 0.649122807018, fp:0.508771929825, fn:0.19298245614 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 36][batch 2 of 8][cntStep: 290] : 0.98\n",
      "Validation accuracy is: 0.614035087719, fp:0.543859649123, fn:0.228070175439 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 37][batch 4 of 8][cntStep: 300] : 1.0\n",
      "Validation accuracy is: 0.701754385965, fp:0.315789473684, fn:0.280701754386 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 38][batch 6 of 8][cntStep: 310] : 1.0\n",
      "Validation accuracy is: 0.684210526316, fp:0.245614035088, fn:0.385964912281 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 40][batch 0 of 8][cntStep: 320] : 1.0\n",
      "Validation accuracy is: 0.666666666667, fp:0.263157894737, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 41][batch 2 of 8][cntStep: 330] : 0.96\n",
      "Validation accuracy is: 0.649122807018, fp:0.315789473684, fn:0.385964912281 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 42][batch 4 of 8][cntStep: 340] : 1.0\n",
      "Validation accuracy is: 0.69298245614, fp:0.263157894737, fn:0.350877192982 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 43][batch 6 of 8][cntStep: 350] : 0.979167\n",
      "Validation accuracy is: 0.631578947368, fp:0.280701754386, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 45][batch 0 of 8][cntStep: 360] : 1.0\n",
      "Validation accuracy is: 0.675438596491, fp:0.245614035088, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 46][batch 2 of 8][cntStep: 370] : 1.0\n",
      "Validation accuracy is: 0.684210526316, fp:0.228070175439, fn:0.40350877193 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 47][batch 4 of 8][cntStep: 380] : 0.98\n",
      "Validation accuracy is: 0.649122807018, fp:0.245614035088, fn:0.456140350877 on shape (114, 100, 100)\n",
      "Training accuracy at [iter 48][batch 6 of 8][cntStep: 390] : 1.0\n",
      "Validation accuracy is: 0.59649122807, fp:0.245614035088, fn:0.561403508772 on shape (114, 100, 100)\n",
      "Best Testing accuracy is:  0.701754385965  on shape  (114, 100, 100)\n"
     ]
    }
   ],
   "source": [
    "train_BiGRU()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "def plot_results(y_label='Percentage(%)'):\n",
    "    N = 3\n",
    "    fold1_best = {'acc': 0.754385964912, 'fp': 0.263157894737, 'fn': 0.228070175439}\n",
    "    fold2_best = {'acc': 0.710526315789, 'fp': 0.315789473684, 'fn': 0.263157894737}\n",
    "    fold3_best = {'acc': 0.728070175439, 'fp': 0.245614035088, 'fn': 0.298245614035}\n",
    "    fold4_best = {'acc': 0.675438596491, 'fp': 0.105263157895, 'fn': 0.543859649123}\n",
    "    fold5_best = {'acc': 0.684210526316, 'fp': 0.543859649123, 'fn': 0.0877192982456}\n",
    "\n",
    "    \n",
    "    folds = [fold1_best, fold2_best, fold3_best, fold4_best, fold5_best]\n",
    "    accs = np.array([e['acc'] for e in folds])*100\n",
    "    mean_acc, std_acc = np.mean(accs), np.std(accs)\n",
    "    \n",
    "    fprs = np.array([e['fp'] for e in folds]) * 100\n",
    "    mean_fp, std_fp = np.mean(fprs), np.std(fprs)\n",
    "    \n",
    "    fnrs = np.array([e['fn'] for e in folds]) * 100\n",
    "    mean_fn, std_fn = np.mean(fnrs), np.std(fnrs)\n",
    "    \n",
    "    ind = np.arange(N) # the x locations for the groups\n",
    "    width = 0.1  # the width of the bars\n",
    "    x = 1\n",
    "    fig, ax = plt.subplots()\n",
    "    rects1 = ax.bar(1, mean_acc,width=0.2,color='#FF9F00',align='center', label='accuracy', yerr=std_acc, error_kw=dict(ecolor='black', lw=4, capsize=6, capthick=2))\n",
    "    rects2 = ax.bar(2, mean_fp,width=0.2,color='#40FFBF',align='center', label='false positive rate', yerr=std_fp, error_kw=dict(ecolor='black', lw=4, capsize=6, capthick=2))\n",
    "    rects3 = ax.bar(3, mean_fn,width=0.2,color='#800000',align='center', label='false negative rate', yerr=std_fn, error_kw=dict(ecolor='black', lw=4, capsize=6, capthick=2))\n",
    "    print(\"Mean acc: \", mean_acc, \"Mean FP: \", mean_fp, \"Mean FN: \", mean_fn)\n",
    "    ax.set_ylabel(y_label, fontsize=20)\n",
    "    ax.set_xlabel(\"Metrics\")\n",
    "\n",
    "    ax.set_xticklabels(('', '', ''))\n",
    "\n",
    "    ax.set_ylim(0, 100)\n",
    "    plt.legend((rects1[0], rects2[0], rects3[0]), ('Accuracy', 'FPR','FNR'), loc=1)\n",
    "    plt.grid(True, linestyle='--', axis='y')\n",
    "    font = {'family': 'normal',\n",
    "            'size': 20}\n",
    "    plt.rc('font', **font)\n",
    "\n",
    "    plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean acc:  71.0526315789 Mean FP:  29.4736842105 Mean FN:  28.4210526316\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nkvo/tensorflow3.5/lib/python3.5/site-packages/matplotlib/font_manager.py:1320: UserWarning: findfont: Font family ['normal'] not found. Falling back to DejaVu Sans\n",
      "  (prop.get_family(), self.defaultFamily[fontext]))\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb09808cb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualization based on attention weights\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def getIndexOfWord(selected_words_file='out_top_16K_words_file.txt'):\n",
    "    fin = open(selected_words_file, 'r')\n",
    "    cnt = 1\n",
    "    dict_reverse_words = {}\n",
    "    dict_selected_words = {}\n",
    "    for line in fin:\n",
    "        _, w, _ = line.split()\n",
    "        dict_selected_words[w] = cnt\n",
    "        dict_reverse_words[cnt] = w\n",
    "        cnt += 1\n",
    "    assert len(dict_selected_words) == 16000 and max(dict_selected_words.values()) == 16000\n",
    "    fin.close()\n",
    "    return dict_reverse_words\n",
    "def visualization_attention():\n",
    "    dict_reverse_words = getIndexOfWord()\n",
    "    MODEL_PATH = \"saved_models/bestBiGRU_attention_log_result_0\"\n",
    "    # Calculate alpha coefficients for the first test example\n",
    "    components, placeholder_input = buildModel()\n",
    "    batch_sent_ph, y_ph, sentence_length_ph, doc_actual_length_ph, valVal_ph = placeholder_input\n",
    "    _, _, _, _, _, _, _, predicted, alphas_first, alphas_second = components\n",
    "    saver = tf.train.Saver()\n",
    "    \n",
    "    num_docs = 20\n",
    "    \n",
    "    with tf.Session() as sess:\n",
    "#         saver.restore(sess, MODEL_PATH)\n",
    "        \n",
    "        saver.restore(sess, \"saved_models/bestBiGRU_attention_log_result_0\")\n",
    "        _, _, X_test, y_test = dict_folds[0]\n",
    "        x_batch_test, y_batch_test = X_test[:num_docs], y_test[:num_docs]\n",
    "\n",
    "        temp = np.sum(x_batch_test, axis=2)\n",
    "        doc_actual_lengths_test = np.count_nonzero(temp, axis=1) \n",
    "        x_batch_reshaped = x_batch_test.reshape(-1, MAX_SENT_LENGTH)\n",
    "        sentence_actual_lengths_test = np.count_nonzero(x_batch_reshaped, axis=1)\n",
    "\n",
    "        alphas_first_test, alphas_second_test, predicted = sess.run([alphas_first, alphas_second, predicted], \n",
    "                                                           feed_dict={batch_sent_ph: x_batch_reshaped, \n",
    "                                                                      y_ph: y_batch_test, sentence_length_ph: sentence_actual_lengths_test,\n",
    "                                                                      doc_actual_length_ph: doc_actual_lengths_test})\n",
    "        #print(alphas_first_test.shape)\n",
    "        alphas_first_test = alphas_first_test.reshape(num_docs, -1, MAX_SENT_LENGTH)\n",
    "        #print(alphas_first_test.shape)\n",
    "        #print(alphas_second_test.shape)\n",
    "        K = 10\n",
    "        max_words = 20\n",
    "        html_file = open(\"visualization.html\", \"w\")\n",
    "        for i in range(num_docs):\n",
    "            label = None\n",
    "            if y_batch_test[i][0] == 1:\n",
    "                label = 'True News'\n",
    "            else:\n",
    "                label = 'Fake News'\n",
    "            predicted_label = None\n",
    "            assert predicted[i] == 1 or predicted[i] == 0\n",
    "            if predicted[i] == 1:\n",
    "                predicted_label = 'Fake'\n",
    "            else:\n",
    "                predicted_label = 'Legitimate'\n",
    "            html_file.write('<div><b>Document %s - Label: %s - Predicted: %s</b></div>\\n' % (i, label, predicted_label))\n",
    "            weights_of_sents = alphas_second_test[i, :]\n",
    "            weights_of_sents /= np.max(weights_of_sents)\n",
    "            assert weights_of_sents.shape == (MAX_SENTS, )\n",
    "            #reshape\n",
    "            alphas_first_test = alphas_first_test.reshape(num_docs, -1, MAX_SENT_LENGTH)\n",
    "            #get top K sentences with highest weights\n",
    "#             topKsents = weights_of_sents.argsort()[-K:][::-1]\n",
    "            topKsents = np.arange(K)\n",
    "            #print(topKsents)\n",
    "            #print(weights_of_sents[topKsents])\n",
    "            for j in topKsents:\n",
    "                weight_of_sent = weights_of_sents[j]\n",
    "                weights_of_words = alphas_first_test[i][j]\n",
    "                testing_sent = x_batch_test[i][j]\n",
    "                \n",
    "                assert weights_of_words.shape == (MAX_SENT_LENGTH, )\n",
    "                weights_of_words /= np.max(weights_of_words)\n",
    "                weights_of_words *= weight_of_sent\n",
    "                #get top max_words with highest weights\n",
    "#                 top_word_index = weights_of_words.argsort()[-max_words:][::-1]\n",
    "                #get weights\n",
    "#                 top_word_weights = weights_of_words[top_word_index]\n",
    "                html_file.write('<span style=\"background: rgba(255, 0, 0, %f);width: 10px;height: 10px;display:inline-block;\"></span> ' % weight_of_sent)\n",
    "                for idx, word_index in enumerate(testing_sent):\n",
    "                    if word_index != 0:\n",
    "                        word = dict_reverse_words[word_index]\n",
    "                        its_weight = weights_of_words[idx]\n",
    "#                         print(dict_reverse_words[word_index], weights_of_words[idx])\n",
    "                        html_file.write('<span style=\"background: rgba(0, 255, 0, %f)\">%s</span> ' % (its_weight, word))\n",
    "                html_file.write(\"<span>. </span>\")\n",
    "                html_file.write(\"<div> </div>\")\n",
    "\n",
    "            \n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from saved_models/bestBiGRU_attention_log_result_0\n"
     ]
    }
   ],
   "source": [
    "from IPython.display import IFrame, HTML\n",
    "visualization_attention()\n",
    "# IFrame('visualization.html', width=1000, height=350)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "scrolled": false
   },
   "source": [
    "<div w3-include-html=\"visualization.html\"></div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<div w3-include-html=\"visualization.html\"></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What is shown in file \"visualization.html\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div w3-include-html=\"visualization.html\"></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<html>\n",
    "<div><b>Document 0 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.017166);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000410)\">musician</span> <span style=\"background: rgba(0, 255, 0, 0.017166)\">hank</span> <span style=\"background: rgba(0, 255, 0, 0.001865)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.001212)\">endorsed</span> <span style=\"background: rgba(0, 255, 0, 0.000789)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000500)\">clinton</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.307560);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.006295)\">june</span> <span style=\"background: rgba(0, 255, 0, 0.293221)\">nevada</span> <span style=\"background: rgba(0, 255, 0, 0.076915)\">county</span> <span style=\"background: rgba(0, 255, 0, 0.061943)\">scooper</span> <span style=\"background: rgba(0, 255, 0, 0.053401)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.041578)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.038937)\">reporting</span> <span style=\"background: rgba(0, 255, 0, 0.038374)\">musician</span> <span style=\"background: rgba(0, 255, 0, 0.304139)\">hank</span> <span style=\"background: rgba(0, 255, 0, 0.055270)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.040038)\">endorsed</span> <span style=\"background: rgba(0, 255, 0, 0.030711)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.024484)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.017995)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.018661)\">united</span> <span style=\"background: rgba(0, 255, 0, 0.014603)\">states</span> <span style=\"background: rgba(0, 255, 0, 0.012863)\">act</span> <span style=\"background: rgba(0, 255, 0, 0.015139)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.009266)\">quite</span> <span style=\"background: rgba(0, 255, 0, 0.013458)\">given</span> <span style=\"background: rgba(0, 255, 0, 0.012437)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.014465)\">long</span> <span style=\"background: rgba(0, 255, 0, 0.010300)\">politically</span> <span style=\"background: rgba(0, 255, 0, 0.012224)\">involved</span> <span style=\"background: rgba(0, 255, 0, 0.014933)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.023617)\">country</span> <span style=\"background: rgba(0, 255, 0, 0.022112)\">music</span> <span style=\"background: rgba(0, 255, 0, 0.027715)\">artist</span> <span style=\"background: rgba(0, 255, 0, 0.307560)\">hank</span> <span style=\"background: rgba(0, 255, 0, 0.087462)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.063804)\">son</span> <span style=\"background: rgba(0, 255, 0, 0.060358)\">legend</span> <span style=\"background: rgba(0, 255, 0, 0.259405)\">hank</span> <span style=\"background: rgba(0, 255, 0, 0.032035)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.011897)\">startling</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.157974);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.074657)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.101035)\">withdrawn</span> <span style=\"background: rgba(0, 255, 0, 0.115625)\">support</span> <span style=\"background: rgba(0, 255, 0, 0.090526)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.133499)\">candidate</span> <span style=\"background: rgba(0, 255, 0, 0.157974)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.105155)\">endorsed</span> <span style=\"background: rgba(0, 255, 0, 0.108688)\">democrat</span> <span style=\"background: rgba(0, 255, 0, 0.089512)\">nominee</span> <span style=\"background: rgba(0, 255, 0, 0.049335)\">hillary</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.076315);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.024451)\">move</span> <span style=\"background: rgba(0, 255, 0, 0.028988)\">shocks</span> <span style=\"background: rgba(0, 255, 0, 0.054036)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.076315)\">fans</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.052857);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.050401)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.052857)\">piece</span> <span style=\"background: rgba(0, 255, 0, 0.037146)\">fabricated</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.338894);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.338894)\">nevada</span> <span style=\"background: rgba(0, 255, 0, 0.056515)\">county</span> <span style=\"background: rgba(0, 255, 0, 0.037511)\">scooper</span> <span style=\"background: rgba(0, 255, 0, 0.020537)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.015241)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.012131)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.008766)\">disclaimer</span> <span style=\"background: rgba(0, 255, 0, 0.010852)\">scooper</span> <span style=\"background: rgba(0, 255, 0, 0.006489)\">satirical</span> <span style=\"background: rgba(0, 255, 0, 0.006355)\">website</span> <span style=\"background: rgba(0, 255, 0, 0.003551)\">scope</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.113150);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.113150)\">sometimes</span> <span style=\"background: rgba(0, 255, 0, 0.080647)\">often</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.081012);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.036499)\">provide</span> <span style=\"background: rgba(0, 255, 0, 0.046225)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.058237)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.064049)\">social</span> <span style=\"background: rgba(0, 255, 0, 0.081012)\">criticism</span> <span style=\"background: rgba(0, 255, 0, 0.053863)\">satirical</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.100196);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.038270)\">intention</span> <span style=\"background: rgba(0, 255, 0, 0.060669)\">fool</span> <span style=\"background: rgba(0, 255, 0, 0.062882)\">trick</span> <span style=\"background: rgba(0, 255, 0, 0.091184)\">obviously</span> <span style=\"background: rgba(0, 255, 0, 0.100196)\">firmly</span> <span style=\"background: rgba(0, 255, 0, 0.091741)\">believe</span> <span style=\"background: rgba(0, 255, 0, 0.078077)\">persons</span> <span style=\"background: rgba(0, 255, 0, 0.097224)\">willingness</span> <span style=\"background: rgba(0, 255, 0, 0.063095)\">listen</span> <span style=\"background: rgba(0, 255, 0, 0.072471)\">injecting</span> <span style=\"background: rgba(0, 255, 0, 0.059952)\">yes</span> <span style=\"background: rgba(0, 255, 0, 0.051225)\">sometimes</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.774711)\">although</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">hank</span> <span style=\"background: rgba(0, 255, 0, 0.181186)\">williams</span> <span style=\"background: rgba(0, 255, 0, 0.126550)\">endorsed</span> <span style=\"background: rgba(0, 255, 0, 0.093756)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.072094)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.050648)\">writing</span> <span style=\"background: rgba(0, 255, 0, 0.052620)\">country</span> <span style=\"background: rgba(0, 255, 0, 0.032826)\">music</span> <span style=\"background: rgba(0, 255, 0, 0.031439)\">star</span> <span style=\"background: rgba(0, 255, 0, 0.035924)\">pledged</span> <span style=\"background: rgba(0, 255, 0, 0.041058)\">support</span> <span style=\"background: rgba(0, 255, 0, 0.029586)\">gop</span> <span style=\"background: rgba(0, 255, 0, 0.031762)\">candidate</span> <span style=\"background: rgba(0, 255, 0, 0.033480)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.030261)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.023117)\">telling</span> <span style=\"background: rgba(0, 255, 0, 0.009648)\">rolling</span> <span style=\"background: rgba(0, 255, 0, 0.009860)\">stone</span> <span style=\"background: rgba(0, 255, 0, 0.004982)\">february</span> <span>. </span><div> </div><div><b>Document 1 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000424);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000327)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.000368)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.000424)\">cow</span> <span style=\"background: rgba(0, 255, 0, 0.000253)\">eyeballs</span> <span style=\"background: rgba(0, 255, 0, 0.000201)\">rectum</span> <span style=\"background: rgba(0, 255, 0, 0.000244)\">arresting</span> <span style=\"background: rgba(0, 255, 0, 0.000171)\">drunk</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.045909);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000615)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.000947)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.001509)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.002718)\">crazed</span> <span style=\"background: rgba(0, 255, 0, 0.002919)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.003327)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.004295)\">reporting</span> <span style=\"background: rgba(0, 255, 0, 0.006196)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.039054)\">wyoming</span> <span style=\"background: rgba(0, 255, 0, 0.007056)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.005474)\">cow</span> <span style=\"background: rgba(0, 255, 0, 0.002978)\">eyeballs</span> <span style=\"background: rgba(0, 255, 0, 0.002479)\">man</span> <span style=\"background: rgba(0, 255, 0, 0.001851)\">named</span> <span style=\"background: rgba(0, 255, 0, 0.001725)\">roy</span> <span style=\"background: rgba(0, 255, 0, 0.002207)\">tilbotts</span> <span style=\"background: rgba(0, 255, 0, 0.001868)\">rectum</span> <span style=\"background: rgba(0, 255, 0, 0.003506)\">stopped</span> <span style=\"background: rgba(0, 255, 0, 0.003938)\">suspicion</span> <span style=\"background: rgba(0, 255, 0, 0.003074)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.003902)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.003730)\">routine</span> <span style=\"background: rgba(0, 255, 0, 0.002807)\">traffic</span> <span style=\"background: rgba(0, 255, 0, 0.002835)\">stop</span> <span style=\"background: rgba(0, 255, 0, 0.002847)\">early</span> <span style=\"background: rgba(0, 255, 0, 0.003269)\">thursday</span> <span style=\"background: rgba(0, 255, 0, 0.003965)\">morning</span> <span style=\"background: rgba(0, 255, 0, 0.004638)\">got</span> <span style=\"background: rgba(0, 255, 0, 0.041835)\">bargained</span> <span style=\"background: rgba(0, 255, 0, 0.012227)\">roy</span> <span style=\"background: rgba(0, 255, 0, 0.014152)\">stepped</span> <span style=\"background: rgba(0, 255, 0, 0.012699)\">el</span> <span style=\"background: rgba(0, 255, 0, 0.045909)\">camino</span> <span style=\"background: rgba(0, 255, 0, 0.014460)\">field</span> <span style=\"background: rgba(0, 255, 0, 0.009449)\">sobriety</span> <span style=\"background: rgba(0, 255, 0, 0.005722)\">test</span> <span style=\"background: rgba(0, 255, 0, 0.003423)\">casper</span> <span style=\"background: rgba(0, 255, 0, 0.002547)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.002071)\">noticed</span> <span style=\"background: rgba(0, 255, 0, 0.001652)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.001905)\">eyeballs</span> <span style=\"background: rgba(0, 255, 0, 0.002198)\">slide</span> <span style=\"background: rgba(0, 255, 0, 0.004934)\">right</span> <span style=\"background: rgba(0, 255, 0, 0.028459)\">pant</span> <span style=\"background: rgba(0, 255, 0, 0.002265)\">leg</span> <span style=\"background: rgba(0, 255, 0, 0.001214)\">onto</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.034887);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.016734)\">feeling</span> <span style=\"background: rgba(0, 255, 0, 0.019871)\">could</span> <span style=\"background: rgba(0, 255, 0, 0.022338)\">potential</span> <span style=\"background: rgba(0, 255, 0, 0.024415)\">murderer</span> <span style=\"background: rgba(0, 255, 0, 0.034887)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.030586)\">quickly</span> <span style=\"background: rgba(0, 255, 0, 0.026739)\">drew</span> <span style=\"background: rgba(0, 255, 0, 0.022159)\">guns</span> <span style=\"background: rgba(0, 255, 0, 0.020175)\">cuffed</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.010810)\">tilbott</span> <span style=\"background: rgba(0, 255, 0, 0.024876)\">assured</span> <span style=\"background: rgba(0, 255, 0, 0.035507)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.040813)\">eyeballs</span> <span style=\"background: rgba(0, 255, 0, 0.067859)\">instead</span> <span style=\"background: rgba(0, 255, 0, 0.089332)\">cow</span> <span style=\"background: rgba(0, 255, 0, 0.084393)\">eyeballs</span> <span style=\"background: rgba(0, 255, 0, 0.166976)\">johnson</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">meats</span> <span style=\"background: rgba(0, 255, 0, 0.095648)\">tilbott</span> <span style=\"background: rgba(0, 255, 0, 0.070064)\">employed</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.613988);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.169055)\">company</span> <span style=\"background: rgba(0, 255, 0, 0.184608)\">wont</span> <span style=\"background: rgba(0, 255, 0, 0.283446)\">let</span> <span style=\"background: rgba(0, 255, 0, 0.340850)\">us</span> <span style=\"background: rgba(0, 255, 0, 0.613988)\">take</span> <span style=\"background: rgba(0, 255, 0, 0.493862)\">animal</span> <span style=\"background: rgba(0, 255, 0, 0.336828)\">home</span> <span style=\"background: rgba(0, 255, 0, 0.414046)\">instead</span> <span style=\"background: rgba(0, 255, 0, 0.341977)\">toss</span> <span style=\"background: rgba(0, 255, 0, 0.219407)\">tilbott</span> <span style=\"background: rgba(0, 255, 0, 0.233609)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.160497)\">police</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.200567);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.200567)\">theyre</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.191710);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.122508)\">allowed</span> <span style=\"background: rgba(0, 255, 0, 0.191710)\">take</span> <span style=\"background: rgba(0, 255, 0, 0.135281)\">scrap</span> <span style=\"background: rgba(0, 255, 0, 0.107455)\">meat</span> <span style=\"background: rgba(0, 255, 0, 0.111326)\">parts</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.102810);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.095033)\">company</span> <span style=\"background: rgba(0, 255, 0, 0.098961)\">start</span> <span style=\"background: rgba(0, 255, 0, 0.102810)\">green</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.072120);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.038956)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.072120)\">even</span> <span style=\"background: rgba(0, 255, 0, 0.061218)\">recycling</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.050625);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.030377)\">truth</span> <span style=\"background: rgba(0, 255, 0, 0.032818)\">another</span> <span style=\"background: rgba(0, 255, 0, 0.031040)\">piece</span> <span style=\"background: rgba(0, 255, 0, 0.032724)\">satire</span> <span style=\"background: rgba(0, 255, 0, 0.048843)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.049926)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.050625)\">web</span> <span>. </span><div> </div><div><b>Document 2 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000014);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">people</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">die</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">younger</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000100);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">may</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">scientific</span> <span style=\"background: rgba(0, 255, 0, 0.000035)\">journal</span> <span style=\"background: rgba(0, 255, 0, 0.000048)\">nature</span> <span style=\"background: rgba(0, 255, 0, 0.000074)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.000073)\">brief</span> <span style=\"background: rgba(0, 255, 0, 0.000068)\">report</span> <span style=\"background: rgba(0, 255, 0, 0.000100)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.000075)\">psychologists</span> <span style=\"background: rgba(0, 255, 0, 0.000060)\">titled</span> <span style=\"background: rgba(0, 255, 0, 0.000034)\">live</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.006157);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.006157)\">itpurported</span> <span style=\"background: rgba(0, 255, 0, 0.000591)\">demonstrate</span> <span style=\"background: rgba(0, 255, 0, 0.000552)\">statistically</span> <span style=\"background: rgba(0, 255, 0, 0.000333)\">significant</span> <span style=\"background: rgba(0, 255, 0, 0.000282)\">difference</span> <span style=\"background: rgba(0, 255, 0, 0.000263)\">longevity</span> <span style=\"background: rgba(0, 255, 0, 0.000295)\">right</span> <span style=\"background: rgba(0, 255, 0, 0.000283)\">left</span> <span style=\"background: rgba(0, 255, 0, 0.000192)\">based</span> <span style=\"background: rgba(0, 255, 0, 0.000160)\">data</span> <span style=\"background: rgba(0, 255, 0, 0.000194)\">collected</span> <span style=\"background: rgba(0, 255, 0, 0.000147)\">professional</span> <span style=\"background: rgba(0, 255, 0, 0.000162)\">baseball</span> <span style=\"background: rgba(0, 255, 0, 0.000245)\">investigate</span> <span style=\"background: rgba(0, 255, 0, 0.000264)\">relationship</span> <span style=\"background: rgba(0, 255, 0, 0.003705)\">handedness</span> <span style=\"background: rgba(0, 255, 0, 0.000545)\">age</span> <span style=\"background: rgba(0, 255, 0, 0.000196)\">analysed</span> <span style=\"background: rgba(0, 255, 0, 0.000152)\">baseball</span> <span style=\"background: rgba(0, 255, 0, 0.000157)\">players</span> <span style=\"background: rgba(0, 255, 0, 0.000105)\">listed</span> <span style=\"background: rgba(0, 255, 0, 0.000081)\">baseball</span> <span style=\"background: rgba(0, 255, 0, 0.000085)\">encyclopedia</span> <span style=\"background: rgba(0, 255, 0, 0.000048)\">dates</span> <span style=\"background: rgba(0, 255, 0, 0.000081)\">birth</span> <span style=\"background: rgba(0, 255, 0, 0.000079)\">well</span> <span style=\"background: rgba(0, 255, 0, 0.000056)\">throwing</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">batting</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.061428);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001412)\">subject</span> <span style=\"background: rgba(0, 255, 0, 0.004401)\">assigned</span> <span style=\"background: rgba(0, 255, 0, 0.061428)\">handedness</span> <span style=\"background: rgba(0, 255, 0, 0.012108)\">group</span> <span style=\"background: rgba(0, 255, 0, 0.007374)\">throwing</span> <span style=\"background: rgba(0, 255, 0, 0.004884)\">batting</span> <span style=\"background: rgba(0, 255, 0, 0.003710)\">hand</span> <span style=\"background: rgba(0, 255, 0, 0.003462)\">indicated</span> <span style=\"background: rgba(0, 255, 0, 0.002208)\">change</span> <span style=\"background: rgba(0, 255, 0, 0.001287)\">hand</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.015465);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.009415)\">mean</span> <span style=\"background: rgba(0, 255, 0, 0.015465)\">age</span> <span style=\"background: rgba(0, 255, 0, 0.009910)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.010561)\">years</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.009132);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.009132)\">years</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.188987);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001656)\">authors</span> <span style=\"background: rgba(0, 255, 0, 0.002927)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.002930)\">another</span> <span style=\"background: rgba(0, 255, 0, 0.005090)\">life</span> <span style=\"background: rgba(0, 255, 0, 0.005154)\">equally</span> <span style=\"background: rgba(0, 255, 0, 0.004348)\">prestigious</span> <span style=\"background: rgba(0, 255, 0, 0.004249)\">new</span> <span style=\"background: rgba(0, 255, 0, 0.005297)\">england</span> <span style=\"background: rgba(0, 255, 0, 0.005060)\">journal</span> <span style=\"background: rgba(0, 255, 0, 0.006154)\">medicine</span> <span style=\"background: rgba(0, 255, 0, 0.005921)\">sampling</span> <span style=\"background: rgba(0, 255, 0, 0.004743)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.005222)\">records</span> <span style=\"background: rgba(0, 255, 0, 0.008581)\">year</span> <span style=\"background: rgba(0, 255, 0, 0.009996)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.007362)\">california</span> <span style=\"background: rgba(0, 255, 0, 0.011411)\">demonstrated</span> <span style=\"background: rgba(0, 255, 0, 0.014007)\">argued</span> <span style=\"background: rgba(0, 255, 0, 0.020722)\">even</span> <span style=\"background: rgba(0, 255, 0, 0.021176)\">larger</span> <span style=\"background: rgba(0, 255, 0, 0.024453)\">difference</span> <span style=\"background: rgba(0, 255, 0, 0.188987)\">lifespan</span> <span style=\"background: rgba(0, 255, 0, 0.051951)\">left</span> <span style=\"background: rgba(0, 255, 0, 0.043944)\">right</span> <span style=\"background: rgba(0, 255, 0, 0.027180)\">order</span> <span style=\"background: rgba(0, 255, 0, 0.031263)\">test</span> <span style=\"background: rgba(0, 255, 0, 0.029879)\">relation</span> <span style=\"background: rgba(0, 255, 0, 0.140111)\">handedness</span> <span style=\"background: rgba(0, 255, 0, 0.038353)\">life</span> <span style=\"background: rgba(0, 255, 0, 0.017103)\">span</span> <span style=\"background: rgba(0, 255, 0, 0.009508)\">general</span> <span style=\"background: rgba(0, 255, 0, 0.004374)\">obtained</span> <span style=\"background: rgba(0, 255, 0, 0.003165)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.003132)\">certificates</span> <span style=\"background: rgba(0, 255, 0, 0.002416)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.001541)\">counties</span> <span style=\"background: rgba(0, 255, 0, 0.001141)\">southern</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.513195);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.009944)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.010030)\">thousand</span> <span style=\"background: rgba(0, 255, 0, 0.019418)\">questionnaires</span> <span style=\"background: rgba(0, 255, 0, 0.030465)\">concerning</span> <span style=\"background: rgba(0, 255, 0, 0.513195)\">handedness</span> <span style=\"background: rgba(0, 255, 0, 0.087216)\">deceased</span> <span style=\"background: rgba(0, 255, 0, 0.079299)\">family</span> <span style=\"background: rgba(0, 255, 0, 0.055294)\">member</span> <span style=\"background: rgba(0, 255, 0, 0.033865)\">sent</span> <span style=\"background: rgba(0, 255, 0, 0.022141)\">listed</span> <span style=\"background: rgba(0, 255, 0, 0.019839)\">next</span> <span style=\"background: rgba(0, 255, 0, 0.021650)\">resulted</span> <span style=\"background: rgba(0, 255, 0, 0.017993)\">usable</span> <span style=\"background: rgba(0, 255, 0, 0.010116)\">cases</span> <span style=\"background: rgba(0, 255, 0, 0.007998)\">male</span> <span style=\"background: rgba(0, 255, 0, 0.004598)\">subjects</span> <span style=\"background: rgba(0, 255, 0, 0.003801)\">female</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.145321);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.073651)\">subjects</span> <span style=\"background: rgba(0, 255, 0, 0.126952)\">designated</span> <span style=\"background: rgba(0, 255, 0, 0.116579)\">threw</span> <span style=\"background: rgba(0, 255, 0, 0.108478)\">ball</span> <span style=\"background: rgba(0, 255, 0, 0.145321)\">right</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.077877);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.043985)\">subjects</span> <span style=\"background: rgba(0, 255, 0, 0.077877)\">assigned</span> <span>. </span><div> </div><div><b>Document 3 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.244478);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001967)\">campaign</span> <span style=\"background: rgba(0, 255, 0, 0.002692)\">ad</span> <span style=\"background: rgba(0, 255, 0, 0.002876)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.003958)\">lyndon</span> <span style=\"background: rgba(0, 255, 0, 0.007461)\">johnson</span> <span style=\"background: rgba(0, 255, 0, 0.004336)\">featured</span> <span style=\"background: rgba(0, 255, 0, 0.004659)\">purported</span> <span style=\"background: rgba(0, 255, 0, 0.004567)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.004884)\">voter</span> <span style=\"background: rgba(0, 255, 0, 0.006687)\">expressing</span> <span style=\"background: rgba(0, 255, 0, 0.005749)\">concerns</span> <span style=\"background: rgba(0, 255, 0, 0.004814)\">eerily</span> <span style=\"background: rgba(0, 255, 0, 0.006385)\">echoed</span> <span style=\"background: rgba(0, 255, 0, 0.004666)\">threads</span> <span style=\"background: rgba(0, 255, 0, 0.006052)\">debate</span> <span style=\"background: rgba(0, 255, 0, 0.004369)\">gop</span> <span style=\"background: rgba(0, 255, 0, 0.004732)\">march</span> <span style=\"background: rgba(0, 255, 0, 0.004128)\">facebook</span> <span style=\"background: rgba(0, 255, 0, 0.004801)\">page</span> <span style=\"background: rgba(0, 255, 0, 0.005199)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.006052)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.005536)\">quartz</span> <span style=\"background: rgba(0, 255, 0, 0.008247)\">shared</span> <span style=\"background: rgba(0, 255, 0, 0.013024)\">video</span> <span style=\"background: rgba(0, 255, 0, 0.020158)\">calledconfessions</span> <span style=\"background: rgba(0, 255, 0, 0.188110)\">originally</span> <span style=\"background: rgba(0, 255, 0, 0.044163)\">political</span> <span style=\"background: rgba(0, 255, 0, 0.037172)\">advertisement</span> <span style=\"background: rgba(0, 255, 0, 0.033094)\">clip</span> <span style=\"background: rgba(0, 255, 0, 0.026266)\">rapidly</span> <span style=\"background: rgba(0, 255, 0, 0.024970)\">gained</span> <span style=\"background: rgba(0, 255, 0, 0.032001)\">along</span> <span style=\"background: rgba(0, 255, 0, 0.034301)\">skepticism</span> <span style=\"background: rgba(0, 255, 0, 0.244478)\">viewpoints</span> <span style=\"background: rgba(0, 255, 0, 0.098610)\">expressed</span> <span style=\"background: rgba(0, 255, 0, 0.178679)\">neatly</span> <span style=\"background: rgba(0, 255, 0, 0.031067)\">echoed</span> <span style=\"background: rgba(0, 255, 0, 0.011991)\">political</span> <span style=\"background: rgba(0, 255, 0, 0.005001)\">schisms</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.432945);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.007485)\">var</span> <span style=\"background: rgba(0, 255, 0, 0.016323)\">fjs</span> <span style=\"background: rgba(0, 255, 0, 0.028580)\">js</span> <span style=\"background: rgba(0, 255, 0, 0.432945)\">confessions</span> <span style=\"background: rgba(0, 255, 0, 0.060211)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.048081)\">ad</span> <span style=\"background: rgba(0, 255, 0, 0.028139)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.019333)\">election</span> <span style=\"background: rgba(0, 255, 0, 0.012293)\">going</span> <span style=\"background: rgba(0, 255, 0, 0.010000)\">thanks</span> <span style=\"background: rgba(0, 255, 0, 0.006073)\">uncanny</span> <span style=\"background: rgba(0, 255, 0, 0.004821)\">relevance</span> <span style=\"background: rgba(0, 255, 0, 0.003764)\">presidential</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.629185);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.005167)\">posted</span> <span style=\"background: rgba(0, 255, 0, 0.004839)\">quartz</span> <span style=\"background: rgba(0, 255, 0, 0.009382)\">march</span> <span style=\"background: rgba(0, 255, 0, 0.016663)\">speaker</span> <span style=\"background: rgba(0, 255, 0, 0.013805)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.019946)\">discussed</span> <span style=\"background: rgba(0, 255, 0, 0.021366)\">lifelong</span> <span style=\"background: rgba(0, 255, 0, 0.022030)\">identity</span> <span style=\"background: rgba(0, 255, 0, 0.019702)\">loyal</span> <span style=\"background: rgba(0, 255, 0, 0.015358)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.015968)\">voter</span> <span style=\"background: rgba(0, 255, 0, 0.021181)\">expressing</span> <span style=\"background: rgba(0, 255, 0, 0.020390)\">reservations</span> <span style=\"background: rgba(0, 255, 0, 0.021849)\">candidacy</span> <span style=\"background: rgba(0, 255, 0, 0.028585)\">barry</span> <span style=\"background: rgba(0, 255, 0, 0.026742)\">unsuccessfully</span> <span style=\"background: rgba(0, 255, 0, 0.032721)\">challenged</span> <span style=\"background: rgba(0, 255, 0, 0.028189)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.032620)\">lyndon</span> <span style=\"background: rgba(0, 255, 0, 0.050157)\">johnson</span> <span style=\"background: rgba(0, 255, 0, 0.030173)\">concerns</span> <span style=\"background: rgba(0, 255, 0, 0.026374)\">aired</span> <span style=\"background: rgba(0, 255, 0, 0.026133)\">text</span> <span style=\"background: rgba(0, 255, 0, 0.020403)\">bottom</span> <span style=\"background: rgba(0, 255, 0, 0.024772)\">described</span> <span style=\"background: rgba(0, 255, 0, 0.021556)\">tendency</span> <span style=\"background: rgba(0, 255, 0, 0.021412)\">goldwater</span> <span style=\"background: rgba(0, 255, 0, 0.022918)\">rapidly</span> <span style=\"background: rgba(0, 255, 0, 0.023442)\">reverse</span> <span style=\"background: rgba(0, 255, 0, 0.031853)\">position</span> <span style=\"background: rgba(0, 255, 0, 0.039387)\">deny</span> <span style=\"background: rgba(0, 255, 0, 0.028186)\">statements</span> <span style=\"background: rgba(0, 255, 0, 0.040477)\">key</span> <span style=\"background: rgba(0, 255, 0, 0.043307)\">well</span> <span style=\"background: rgba(0, 255, 0, 0.031912)\">attitude</span> <span style=\"background: rgba(0, 255, 0, 0.062889)\">duringa</span> <span style=\"background: rgba(0, 255, 0, 0.084329)\">point</span> <span style=\"background: rgba(0, 255, 0, 0.084836)\">american</span> <span style=\"background: rgba(0, 255, 0, 0.095999)\">historywhen</span> <span style=\"background: rgba(0, 255, 0, 0.511778)\">specterofnuclear</span> <span style=\"background: rgba(0, 255, 0, 0.163120)\">destruction</span> <span style=\"background: rgba(0, 255, 0, 0.154191)\">hardest</span> <span style=\"background: rgba(0, 255, 0, 0.629185)\">thing</span> <span style=\"background: rgba(0, 255, 0, 0.077672)\">whole</span> <span style=\"background: rgba(0, 255, 0, 0.066142)\">campaign</span> <span style=\"background: rgba(0, 255, 0, 0.033607)\">sort</span> <span style=\"background: rgba(0, 255, 0, 0.019496)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.012280)\">goldwater</span> <span style=\"background: rgba(0, 255, 0, 0.007357)\">statement</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.539882);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.271822)\">reporter</span> <span style=\"background: rgba(0, 255, 0, 0.385026)\">go</span> <span style=\"background: rgba(0, 255, 0, 0.539882)\">senator</span> <span style=\"background: rgba(0, 255, 0, 0.435625)\">goldwater</span> <span style=\"background: rgba(0, 255, 0, 0.390506)\">hell</span> <span style=\"background: rgba(0, 255, 0, 0.308832)\">blah</span> <span style=\"background: rgba(0, 255, 0, 0.219733)\">blah</span> <span style=\"background: rgba(0, 255, 0, 0.155637)\">blah</span> <span style=\"background: rgba(0, 255, 0, 0.139672)\">whatever</span> <span style=\"background: rgba(0, 255, 0, 0.160706)\">end</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.438215);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.366504)\">goldwater</span> <span style=\"background: rgba(0, 255, 0, 0.438215)\">wouldnt</span> <span style=\"background: rgba(0, 255, 0, 0.411097)\">put</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.366881);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.312473)\">cant</span> <span style=\"background: rgba(0, 255, 0, 0.366881)\">follow</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.315932);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.315932)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.310751)\">put</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.298370);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.185978)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.298370)\">says</span> <span style=\"background: rgba(0, 255, 0, 0.286512)\">wouldnt</span> <span style=\"background: rgba(0, 255, 0, 0.230026)\">put</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.254015);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.254015)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.223241)\">get</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.225018);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.225018)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.206020)\">ought</span> <span style=\"background: rgba(0, 255, 0, 0.161882)\">mean</span> <span>. </span><div> </div><div><b>Document 4 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.001367);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001173)\">december</span> <span style=\"background: rgba(0, 255, 0, 0.001096)\">amateur</span> <span style=\"background: rgba(0, 255, 0, 0.001120)\">photographer</span> <span style=\"background: rgba(0, 255, 0, 0.000897)\">snapped</span> <span style=\"background: rgba(0, 255, 0, 0.001167)\">pictures</span> <span style=\"background: rgba(0, 255, 0, 0.001367)\">snow</span> <span style=\"background: rgba(0, 255, 0, 0.001081)\">ground</span> <span style=\"background: rgba(0, 255, 0, 0.001136)\">algerian</span> <span style=\"background: rgba(0, 255, 0, 0.001253)\">city</span> <span style=\"background: rgba(0, 255, 0, 0.000727)\">borders</span> <span style=\"background: rgba(0, 255, 0, 0.000498)\">sahara</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.016098);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000379)\">december</span> <span style=\"background: rgba(0, 255, 0, 0.000389)\">amateur</span> <span style=\"background: rgba(0, 255, 0, 0.000448)\">photographer</span> <span style=\"background: rgba(0, 255, 0, 0.000566)\">posted</span> <span style=\"background: rgba(0, 255, 0, 0.000544)\">album</span> <span style=\"background: rgba(0, 255, 0, 0.000670)\">facebook</span> <span style=\"background: rgba(0, 255, 0, 0.000817)\">images</span> <span style=\"background: rgba(0, 255, 0, 0.000954)\">capturing</span> <span style=\"background: rgba(0, 255, 0, 0.001010)\">snow</span> <span style=\"background: rgba(0, 255, 0, 0.001052)\">algerian</span> <span style=\"background: rgba(0, 255, 0, 0.001347)\">town</span> <span style=\"background: rgba(0, 255, 0, 0.001314)\">located</span> <span style=\"background: rgba(0, 255, 0, 0.001282)\">hills</span> <span style=\"background: rgba(0, 255, 0, 0.016098)\">bordering</span> <span style=\"background: rgba(0, 255, 0, 0.002484)\">sahara</span> <span style=\"background: rgba(0, 255, 0, 0.001274)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.000914)\">online</span> <span style=\"background: rgba(0, 255, 0, 0.000658)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.000496)\">outlets</span> <span style=\"background: rgba(0, 255, 0, 0.000385)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.000237)\">stunning</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.217444);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004613)\">according</span> <span style=\"background: rgba(0, 255, 0, 0.009630)\">last</span> <span style=\"background: rgba(0, 255, 0, 0.011264)\">significant</span> <span style=\"background: rgba(0, 255, 0, 0.217444)\">snowfall</span> <span style=\"background: rgba(0, 255, 0, 0.063068)\">occurred</span> <span style=\"background: rgba(0, 255, 0, 0.044618)\">area</span> <span style=\"background: rgba(0, 255, 0, 0.038271)\">february</span> <span style=\"background: rgba(0, 255, 0, 0.044243)\">last</span> <span style=\"background: rgba(0, 255, 0, 0.034635)\">major</span> <span style=\"background: rgba(0, 255, 0, 0.210463)\">snowfall</span> <span style=\"background: rgba(0, 255, 0, 0.044616)\">called</span> <span style=\"background: rgba(0, 255, 0, 0.019592)\">hit</span> <span style=\"background: rgba(0, 255, 0, 0.010162)\">sefra</span> <span style=\"background: rgba(0, 255, 0, 0.006006)\">february</span> <span style=\"background: rgba(0, 255, 0, 0.003381)\">snowed</span> <span style=\"background: rgba(0, 255, 0, 0.002658)\">whopping</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.810361);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004034)\">subsequent</span> <span style=\"background: rgba(0, 255, 0, 0.006393)\">snow</span> <span style=\"background: rgba(0, 255, 0, 0.007929)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.011633)\">appeared</span> <span style=\"background: rgba(0, 255, 0, 0.014334)\">viewers</span> <span style=\"background: rgba(0, 255, 0, 0.022816)\">expressed</span> <span style=\"background: rgba(0, 255, 0, 0.037312)\">skepticism</span> <span style=\"background: rgba(0, 255, 0, 0.049126)\">authenticity</span> <span style=\"background: rgba(0, 255, 0, 0.073357)\">photographs</span> <span style=\"background: rgba(0, 255, 0, 0.810361)\">likelihood</span> <span style=\"background: rgba(0, 255, 0, 0.162871)\">town</span> <span style=\"background: rgba(0, 255, 0, 0.088279)\">located</span> <span style=\"background: rgba(0, 255, 0, 0.058455)\">next</span> <span style=\"background: rgba(0, 255, 0, 0.040482)\">sahara</span> <span style=\"background: rgba(0, 255, 0, 0.041256)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.018774)\">see</span> <span style=\"background: rgba(0, 255, 0, 0.013182)\">snow</span> <span style=\"background: rgba(0, 255, 0, 0.009904)\">first</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.006283)\">fact</span> <span style=\"background: rgba(0, 255, 0, 0.007092)\">snowed</span> <span style=\"background: rgba(0, 255, 0, 0.009720)\">sefra</span> <span style=\"background: rgba(0, 255, 0, 0.019898)\">december</span> <span style=\"background: rgba(0, 255, 0, 0.018761)\">via</span> <span style=\"background: rgba(0, 255, 0, 0.028202)\">nasa</span> <span style=\"background: rgba(0, 255, 0, 0.031306)\">satellite</span> <span style=\"background: rgba(0, 255, 0, 0.040021)\">data</span> <span style=\"background: rgba(0, 255, 0, 0.083546)\">shows</span> <span style=\"background: rgba(0, 255, 0, 0.079799)\">pockets</span> <span style=\"background: rgba(0, 255, 0, 0.131077)\">snow</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">snowfall</span> <span style=\"background: rgba(0, 255, 0, 0.227890)\">indeed</span> <span style=\"background: rgba(0, 255, 0, 0.145451)\">rare</span> <span style=\"background: rgba(0, 255, 0, 0.122157)\">occurrence</span> <span style=\"background: rgba(0, 255, 0, 0.120912)\">temperatures</span> <span style=\"background: rgba(0, 255, 0, 0.090228)\">led</span> <span style=\"background: rgba(0, 255, 0, 0.047290)\">air</span> <span style=\"background: rgba(0, 255, 0, 0.031795)\">cool</span> <span style=\"background: rgba(0, 255, 0, 0.021474)\">enough</span> <span style=\"background: rgba(0, 255, 0, 0.013494)\">produce</span> <span style=\"background: rgba(0, 255, 0, 0.010486)\">snow</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.482748);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.079102)\">historical</span> <span style=\"background: rgba(0, 255, 0, 0.104303)\">data</span> <span style=\"background: rgba(0, 255, 0, 0.131259)\">region</span> <span style=\"background: rgba(0, 255, 0, 0.235914)\">show</span> <span style=\"background: rgba(0, 255, 0, 0.361564)\">december</span> <span style=\"background: rgba(0, 255, 0, 0.376714)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.482748)\">temperatures</span> <span style=\"background: rgba(0, 255, 0, 0.189351)\">often</span> <span style=\"background: rgba(0, 255, 0, 0.169568)\">dip</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000046);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000046);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000046);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000046);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><div><b>Document 5 - Label: Fake News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">member</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">board</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">bet</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">dare</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">ask</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">serving</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000020);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">walmart</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">chain</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">retail</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">stores</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">monsanto</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">biotechnology</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">corporation</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">americas</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">largest</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">theyre</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">businesses</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">mostly</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">frequently</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">invoked</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">public</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">criticism</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">supposed</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">corporate</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">putting</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">profits</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">growth</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">far</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">ahead</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">concern</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000012);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">due</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">public</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">politicians</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">democratic</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">populist</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">risk</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">among</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">supporters</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">significant</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">business</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">ties</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">campaign</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000012);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">hence</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">recent</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">point</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">criticism</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">democratic</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">candidate</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">sit</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">board</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">directors</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">walmart</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000024);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">true</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">thirty</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">years</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">ago</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">began</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">tenure</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">member</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">walmarts</span> <span style=\"background: rgba(0, 255, 0, 0.000022)\">board</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">aspect</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">past</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">largely</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">avoided</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">mentioning</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">campaign</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">sam</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">founder</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000023);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">growing</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">pressure</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">shareholders</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">helen</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">appoint</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">woman</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">companys</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">board</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000029);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">walton</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">turned</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">young</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">lawyer</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">happened</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">married</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">governor</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">rodham</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000031);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.000016)\">tenure</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">director</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">nations</span> <span style=\"background: rgba(0, 255, 0, 0.000028)\">largest</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">remains</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">little</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">known</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">chapter</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">closely</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000018);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">little</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">known</span> <span>. </span><div> </div><div><b>Document 6 - Label: Fake News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000242);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000105)\">video</span> <span style=\"background: rgba(0, 255, 0, 0.000191)\">clip</span> <span style=\"background: rgba(0, 255, 0, 0.000242)\">shows</span> <span style=\"background: rgba(0, 255, 0, 0.000186)\">meteorite</span> <span style=\"background: rgba(0, 255, 0, 0.000196)\">striking</span> <span style=\"background: rgba(0, 255, 0, 0.000236)\">pickup</span> <span style=\"background: rgba(0, 255, 0, 0.000130)\">truck</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000850);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000352)\">group</span> <span style=\"background: rgba(0, 255, 0, 0.000460)\">recreationists</span> <span style=\"background: rgba(0, 255, 0, 0.000281)\">videotaping</span> <span style=\"background: rgba(0, 255, 0, 0.000272)\">desert</span> <span style=\"background: rgba(0, 255, 0, 0.000406)\">outing</span> <span style=\"background: rgba(0, 255, 0, 0.000616)\">suddenly</span> <span style=\"background: rgba(0, 255, 0, 0.000493)\">spot</span> <span style=\"background: rgba(0, 255, 0, 0.000850)\">something</span> <span style=\"background: rgba(0, 255, 0, 0.000717)\">unusual</span> <span style=\"background: rgba(0, 255, 0, 0.000433)\">sky</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.052933);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.052933)\">flaming</span> <span style=\"background: rgba(0, 255, 0, 0.010105)\">ball</span> <span style=\"background: rgba(0, 255, 0, 0.007946)\">smashes</span> <span style=\"background: rgba(0, 255, 0, 0.005683)\">directly</span> <span style=\"background: rgba(0, 255, 0, 0.003941)\">ground</span> <span style=\"background: rgba(0, 255, 0, 0.003837)\">around</span> <span style=\"background: rgba(0, 255, 0, 0.003712)\">passing</span> <span style=\"background: rgba(0, 255, 0, 0.004589)\">pickup</span> <span style=\"background: rgba(0, 255, 0, 0.004478)\">blast</span> <span style=\"background: rgba(0, 255, 0, 0.004413)\">sending</span> <span style=\"background: rgba(0, 255, 0, 0.029144)\">cameraman</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.027293);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.027293)\">even</span> <span style=\"background: rgba(0, 255, 0, 0.019396)\">truck</span> <span style=\"background: rgba(0, 255, 0, 0.023953)\">apparently</span> <span style=\"background: rgba(0, 255, 0, 0.021871)\">unscathed</span> <span style=\"background: rgba(0, 255, 0, 0.026363)\">promptly</span> <span style=\"background: rgba(0, 255, 0, 0.024070)\">starting</span> <span style=\"background: rgba(0, 255, 0, 0.018775)\">driving</span> <span style=\"background: rgba(0, 255, 0, 0.023795)\">cheers</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.019581);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.019581)\">astounding</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.026124);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.017211)\">another</span> <span style=\"background: rgba(0, 255, 0, 0.026124)\">case</span> <span style=\"background: rgba(0, 255, 0, 0.021866)\">edited</span> <span style=\"background: rgba(0, 255, 0, 0.021245)\">television</span> <span style=\"background: rgba(0, 255, 0, 0.023814)\">commercial</span> <span style=\"background: rgba(0, 255, 0, 0.013113)\">presented</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.512070);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.006816)\">clip</span> <span style=\"background: rgba(0, 255, 0, 0.009164)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.014784)\">tv</span> <span style=\"background: rgba(0, 255, 0, 0.027524)\">commercial</span> <span style=\"background: rgba(0, 255, 0, 0.037354)\">advertising</span> <span style=\"background: rgba(0, 255, 0, 0.512070)\">toyota</span> <span style=\"background: rgba(0, 255, 0, 0.045683)\">produced</span> <span style=\"background: rgba(0, 255, 0, 0.023409)\">automaker</span> <span style=\"background: rgba(0, 255, 0, 0.015163)\">method</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.012807)\">full</span> <span style=\"background: rgba(0, 255, 0, 0.021257)\">clip</span> <span style=\"background: rgba(0, 255, 0, 0.026259)\">plainly</span> <span style=\"background: rgba(0, 255, 0, 0.041458)\">displays</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">toyota</span> <span style=\"background: rgba(0, 255, 0, 0.074166)\">name</span> <span style=\"background: rgba(0, 255, 0, 0.033000)\">logo</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000084);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000084);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><div><b>Document 7 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000197);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000156)\">photograph</span> <span style=\"background: rgba(0, 255, 0, 0.000167)\">shows</span> <span style=\"background: rgba(0, 255, 0, 0.000110)\">real</span> <span style=\"background: rgba(0, 255, 0, 0.000163)\">portrait</span> <span style=\"background: rgba(0, 255, 0, 0.000197)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.000166)\">trump</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.033073);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000302)\">august</span> <span style=\"background: rgba(0, 255, 0, 0.000503)\">portrait</span> <span style=\"background: rgba(0, 255, 0, 0.000634)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.000908)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.001307)\">nominee</span> <span style=\"background: rgba(0, 255, 0, 0.001736)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.001951)\">wife</span> <span style=\"background: rgba(0, 255, 0, 0.002117)\">son</span> <span style=\"background: rgba(0, 255, 0, 0.003078)\">barron</span> <span style=\"background: rgba(0, 255, 0, 0.033073)\">photographwascirculated</span> <span style=\"background: rgba(0, 255, 0, 0.006646)\">derisive</span> <span style=\"background: rgba(0, 255, 0, 0.004311)\">comments</span> <span style=\"background: rgba(0, 255, 0, 0.003265)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.001831)\">somewere</span> <span style=\"background: rgba(0, 255, 0, 0.000909)\">convinced</span> <span style=\"background: rgba(0, 255, 0, 0.000599)\">image</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.236702);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002303)\">portrait</span> <span style=\"background: rgba(0, 255, 0, 0.003870)\">part</span> <span style=\"background: rgba(0, 255, 0, 0.004270)\">barron</span> <span style=\"background: rgba(0, 255, 0, 0.006969)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.007185)\">home</span> <span style=\"background: rgba(0, 255, 0, 0.011089)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.015911)\">photographer</span> <span style=\"background: rgba(0, 255, 0, 0.016630)\">regine</span> <span style=\"background: rgba(0, 255, 0, 0.236702)\">mahaux</span> <span style=\"background: rgba(0, 255, 0, 0.046295)\">getty</span> <span style=\"background: rgba(0, 255, 0, 0.022792)\">accompanied</span> <span style=\"background: rgba(0, 255, 0, 0.027773)\">following</span> <span style=\"background: rgba(0, 255, 0, 0.024723)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.015249)\">melania</span> <span style=\"background: rgba(0, 255, 0, 0.015164)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.008256)\">son</span> <span style=\"background: rgba(0, 255, 0, 0.006794)\">barron</span> <span style=\"background: rgba(0, 255, 0, 0.006581)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.004587)\">pose</span> <span style=\"background: rgba(0, 255, 0, 0.003793)\">portrait</span> <span style=\"background: rgba(0, 255, 0, 0.002787)\">april</span> <span style=\"background: rgba(0, 255, 0, 0.002165)\">new</span> <span style=\"background: rgba(0, 255, 0, 0.002063)\">york</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.679444);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.005902)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.009106)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.011298)\">wearing</span> <span style=\"background: rgba(0, 255, 0, 0.012984)\">suit</span> <span style=\"background: rgba(0, 255, 0, 0.011081)\">tie</span> <span style=\"background: rgba(0, 255, 0, 0.013477)\">melania</span> <span style=\"background: rgba(0, 255, 0, 0.018593)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.019395)\">wearing</span> <span style=\"background: rgba(0, 255, 0, 0.018210)\">dress</span> <span style=\"background: rgba(0, 255, 0, 0.017342)\">shoes</span> <span style=\"background: rgba(0, 255, 0, 0.018827)\">makeup</span> <span style=\"background: rgba(0, 255, 0, 0.025831)\">mykel</span> <span style=\"background: rgba(0, 255, 0, 0.054299)\">hair</span> <span style=\"background: rgba(0, 255, 0, 0.620172)\">mordechia</span> <span style=\"background: rgba(0, 255, 0, 0.173485)\">barron</span> <span style=\"background: rgba(0, 255, 0, 0.172963)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.154396)\">wearing</span> <span style=\"background: rgba(0, 255, 0, 0.144890)\">jacket</span> <span style=\"background: rgba(0, 255, 0, 0.679444)\">pants</span> <span style=\"background: rgba(0, 255, 0, 0.347641)\">shirt</span> <span style=\"background: rgba(0, 255, 0, 0.487276)\">leon</span> <span style=\"background: rgba(0, 255, 0, 0.041486)\">shoes</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.346433);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.145321)\">invited</span> <span style=\"background: rgba(0, 255, 0, 0.158455)\">trumps</span> <span style=\"background: rgba(0, 255, 0, 0.197227)\">home</span> <span style=\"background: rgba(0, 255, 0, 0.173011)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.230803)\">occasions</span> <span style=\"background: rgba(0, 255, 0, 0.346433)\">take</span> <span style=\"background: rgba(0, 255, 0, 0.208306)\">photographs</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.009596)\">march</span> <span style=\"background: rgba(0, 255, 0, 0.008391)\">morningpublished</span> <span style=\"background: rgba(0, 255, 0, 0.015289)\">interview</span> <span style=\"background: rgba(0, 255, 0, 0.024557)\">photographer</span> <span style=\"background: rgba(0, 255, 0, 0.030024)\">shared</span> <span style=\"background: rgba(0, 255, 0, 0.047836)\">views</span> <span style=\"background: rgba(0, 255, 0, 0.058421)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.086295)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">mahaux</span> <span style=\"background: rgba(0, 255, 0, 0.185547)\">since</span> <span style=\"background: rgba(0, 255, 0, 0.118721)\">opportunity</span> <span style=\"background: rgba(0, 255, 0, 0.081332)\">immortalize</span> <span style=\"background: rgba(0, 255, 0, 0.051179)\">trumps</span> <span style=\"background: rgba(0, 255, 0, 0.030050)\">repeatedly</span> <span style=\"background: rgba(0, 255, 0, 0.021910)\">series</span> <span style=\"background: rgba(0, 255, 0, 0.019529)\">family</span> <span style=\"background: rgba(0, 255, 0, 0.012783)\">portraits</span> <span style=\"background: rgba(0, 255, 0, 0.007891)\">beginning</span> <span style=\"background: rgba(0, 255, 0, 0.006118)\">presidential</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.975360);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.016580)\">like</span> <span style=\"background: rgba(0, 255, 0, 0.025665)\">working</span> <span style=\"background: rgba(0, 255, 0, 0.046263)\">familys</span> <span style=\"background: rgba(0, 255, 0, 0.057614)\">speaks</span> <span style=\"background: rgba(0, 255, 0, 0.975360)\">inspires</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.406257);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.406257)\">lot</span> <span style=\"background: rgba(0, 255, 0, 0.333282)\">freedom</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.278323);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.166846)\">let</span> <span style=\"background: rgba(0, 255, 0, 0.268204)\">express</span> <span style=\"background: rgba(0, 255, 0, 0.278323)\">says</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.199354);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.094937)\">trumps</span> <span style=\"background: rgba(0, 255, 0, 0.144745)\">far</span> <span style=\"background: rgba(0, 255, 0, 0.199354)\">people</span> <span style=\"background: rgba(0, 255, 0, 0.137417)\">see</span> <span>. </span><div> </div><div><b>Document 8 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000448);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000338)\">starbucks</span> <span style=\"background: rgba(0, 255, 0, 0.000383)\">offered</span> <span style=\"background: rgba(0, 255, 0, 0.000448)\">free</span> <span style=\"background: rgba(0, 255, 0, 0.000356)\">drink</span> <span style=\"background: rgba(0, 255, 0, 0.000283)\">customers</span> <span style=\"background: rgba(0, 255, 0, 0.000248)\">provided</span> <span style=\"background: rgba(0, 255, 0, 0.000204)\">name</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.036901);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000322)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.000385)\">starbucks</span> <span style=\"background: rgba(0, 255, 0, 0.000426)\">announced</span> <span style=\"background: rgba(0, 255, 0, 0.000461)\">planned</span> <span style=\"background: rgba(0, 255, 0, 0.000580)\">hiring</span> <span style=\"background: rgba(0, 255, 0, 0.000621)\">refugees</span> <span style=\"background: rgba(0, 255, 0, 0.000829)\">next</span> <span style=\"background: rgba(0, 255, 0, 0.001038)\">five</span> <span style=\"background: rgba(0, 255, 0, 0.001021)\">years</span> <span style=\"background: rgba(0, 255, 0, 0.001075)\">response</span> <span style=\"background: rgba(0, 255, 0, 0.001076)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.001599)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.001213)\">trumps</span> <span style=\"background: rgba(0, 255, 0, 0.001959)\">immigration</span> <span style=\"background: rgba(0, 255, 0, 0.002138)\">image</span> <span style=\"background: rgba(0, 255, 0, 0.002691)\">appeared</span> <span style=\"background: rgba(0, 255, 0, 0.003025)\">purporting</span> <span style=\"background: rgba(0, 255, 0, 0.036901)\">showa</span> <span style=\"background: rgba(0, 255, 0, 0.006558)\">promotion</span> <span style=\"background: rgba(0, 255, 0, 0.002989)\">say</span> <span style=\"background: rgba(0, 255, 0, 0.001454)\">yes</span> <span style=\"background: rgba(0, 255, 0, 0.000705)\">hiring</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.022535);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.010334)\">enjoy</span> <span style=\"background: rgba(0, 255, 0, 0.013890)\">complimentary</span> <span style=\"background: rgba(0, 255, 0, 0.014079)\">upsize</span> <span style=\"background: rgba(0, 255, 0, 0.016768)\">beverage</span> <span style=\"background: rgba(0, 255, 0, 0.022535)\">purchase</span> <span style=\"background: rgba(0, 255, 0, 0.020343)\">provide</span> <span style=\"background: rgba(0, 255, 0, 0.016883)\">name</span> <span style=\"background: rgba(0, 255, 0, 0.013011)\">aloha</span> <span style=\"background: rgba(0, 255, 0, 0.010991)\">snackbar</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.540553);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.006442)\">image</span> <span style=\"background: rgba(0, 255, 0, 0.011585)\">section</span> <span style=\"background: rgba(0, 255, 0, 0.014625)\">reddit</span> <span style=\"background: rgba(0, 255, 0, 0.024441)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.034735)\">along</span> <span style=\"background: rgba(0, 255, 0, 0.032651)\">messages</span> <span style=\"background: rgba(0, 255, 0, 0.036972)\">encouraging</span> <span style=\"background: rgba(0, 255, 0, 0.059986)\">members</span> <span style=\"background: rgba(0, 255, 0, 0.540553)\">tospread</span> <span style=\"background: rgba(0, 255, 0, 0.126276)\">social</span> <span style=\"background: rgba(0, 255, 0, 0.094256)\">mediato</span> <span style=\"background: rgba(0, 255, 0, 0.076908)\">see</span> <span style=\"background: rgba(0, 255, 0, 0.077130)\">people</span> <span style=\"background: rgba(0, 255, 0, 0.067883)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.041541)\">fall</span> <span style=\"background: rgba(0, 255, 0, 0.025940)\">best</span> <span style=\"background: rgba(0, 255, 0, 0.019909)\">memes</span> <span style=\"background: rgba(0, 255, 0, 0.014730)\">enemy</span> <span style=\"background: rgba(0, 255, 0, 0.007682)\">spreads</span> <span style=\"background: rgba(0, 255, 0, 0.006194)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.004972)\">go</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.163198);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.163198)\">image</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.227916);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.033552)\">real</span> <span style=\"background: rgba(0, 255, 0, 0.062716)\">starbucks</span> <span style=\"background: rgba(0, 255, 0, 0.084434)\">advertisementfrom</span> <span style=\"background: rgba(0, 255, 0, 0.109020)\">whoever</span> <span style=\"background: rgba(0, 255, 0, 0.180038)\">created</span> <span style=\"background: rgba(0, 255, 0, 0.160279)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.227916)\">promotion</span> <span style=\"background: rgba(0, 255, 0, 0.158459)\">simply</span> <span style=\"background: rgba(0, 255, 0, 0.150986)\">deleted</span> <span style=\"background: rgba(0, 255, 0, 0.179684)\">original</span> <span style=\"background: rgba(0, 255, 0, 0.217516)\">text</span> <span style=\"background: rgba(0, 255, 0, 0.201018)\">genuine</span> <span style=\"background: rgba(0, 255, 0, 0.176431)\">starbucks</span> <span style=\"background: rgba(0, 255, 0, 0.157122)\">advertisement</span> <span style=\"background: rgba(0, 255, 0, 0.117509)\">offered</span> <span style=\"background: rgba(0, 255, 0, 0.086182)\">drinks</span> <span style=\"background: rgba(0, 255, 0, 0.070840)\">purchase</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.012043)\">biggest</span> <span style=\"background: rgba(0, 255, 0, 0.017198)\">mistake</span> <span style=\"background: rgba(0, 255, 0, 0.022290)\">letter</span> <span style=\"background: rgba(0, 255, 0, 0.023236)\">word</span> <span style=\"background: rgba(0, 255, 0, 0.027796)\">say</span> <span style=\"background: rgba(0, 255, 0, 0.027804)\">missing</span> <span style=\"background: rgba(0, 255, 0, 0.031688)\">lower</span> <span style=\"background: rgba(0, 255, 0, 0.028286)\">providing</span> <span style=\"background: rgba(0, 255, 0, 0.031831)\">name</span> <span style=\"background: rgba(0, 255, 0, 0.038782)\">aloha</span> <span style=\"background: rgba(0, 255, 0, 0.053294)\">snackbar</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">barista</span> <span style=\"background: rgba(0, 255, 0, 0.140028)\">net</span> <span style=\"background: rgba(0, 255, 0, 0.103117)\">free</span> <span style=\"background: rgba(0, 255, 0, 0.051687)\">anything</span> <span style=\"background: rgba(0, 255, 0, 0.052220)\">help</span> <span style=\"background: rgba(0, 255, 0, 0.025790)\">refugees</span> <span style=\"background: rgba(0, 255, 0, 0.012904)\">anywhere</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000405);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000405);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000405);width: 10px;height: 10px;display:inline-block;\"></span> <span>. </span><div> </div><div><b>Document 9 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000012);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">account</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">apollo</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">astronaut</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">buzz</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">aldrin</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">describes</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">taking</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">communion</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000122);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">smaller</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">details</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">lost</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">amidst</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">tremendous</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">historic</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">scientific</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">achievements</span> <span style=\"background: rgba(0, 255, 0, 0.000122)\">apollo</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">mission</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">landed</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">first</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">human</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">beings</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">moon</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">marked</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">first</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">occasion</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">christian</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">took</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">sacrament</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">communion</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">body</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000646);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">event</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">took</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">place</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">interval</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">lunar</span> <span style=\"background: rgba(0, 255, 0, 0.000038)\">modules</span> <span style=\"background: rgba(0, 255, 0, 0.000047)\">landing</span> <span style=\"background: rgba(0, 255, 0, 0.000050)\">moon</span> <span style=\"background: rgba(0, 255, 0, 0.000044)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.000047)\">neil</span> <span style=\"background: rgba(0, 255, 0, 0.000033)\">taking</span> <span style=\"background: rgba(0, 255, 0, 0.000048)\">first</span> <span style=\"background: rgba(0, 255, 0, 0.000038)\">steps</span> <span style=\"background: rgba(0, 255, 0, 0.000035)\">lunar</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">surface</span> <span style=\"background: rgba(0, 255, 0, 0.000027)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">hours</span> <span style=\"background: rgba(0, 255, 0, 0.000037)\">astronaut</span> <span style=\"background: rgba(0, 255, 0, 0.000048)\">buzz</span> <span style=\"background: rgba(0, 255, 0, 0.000646)\">aldrin</span> <span style=\"background: rgba(0, 255, 0, 0.000113)\">privately</span> <span style=\"background: rgba(0, 255, 0, 0.000101)\">observed</span> <span style=\"background: rgba(0, 255, 0, 0.000054)\">communion</span> <span style=\"background: rgba(0, 255, 0, 0.000040)\">using</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">elements</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">brought</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.002739);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001509)\">aldrin</span> <span style=\"background: rgba(0, 255, 0, 0.000318)\">openly</span> <span style=\"background: rgba(0, 255, 0, 0.000294)\">described</span> <span style=\"background: rgba(0, 255, 0, 0.000227)\">communion</span> <span style=\"background: rgba(0, 255, 0, 0.000205)\">experience</span> <span style=\"background: rgba(0, 255, 0, 0.000238)\">moon</span> <span style=\"background: rgba(0, 255, 0, 0.000205)\">print</span> <span style=\"background: rgba(0, 255, 0, 0.000128)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.000199)\">including</span> <span style=\"background: rgba(0, 255, 0, 0.000195)\">august</span> <span style=\"background: rgba(0, 255, 0, 0.000223)\">interview</span> <span style=\"background: rgba(0, 255, 0, 0.000365)\">life</span> <span style=\"background: rgba(0, 255, 0, 0.000320)\">october</span> <span style=\"background: rgba(0, 255, 0, 0.002739)\">guideposts</span> <span style=\"background: rgba(0, 255, 0, 0.000356)\">book</span> <span style=\"background: rgba(0, 255, 0, 0.000230)\">return</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.012658);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000126)\">following</span> <span style=\"background: rgba(0, 255, 0, 0.000177)\">account</span> <span style=\"background: rgba(0, 255, 0, 0.000445)\">motivations</span> <span style=\"background: rgba(0, 255, 0, 0.000539)\">preparation</span> <span style=\"background: rgba(0, 255, 0, 0.001047)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.012658)\">aldrins</span> <span style=\"background: rgba(0, 255, 0, 0.004370)\">landing</span> <span style=\"background: rgba(0, 255, 0, 0.003725)\">moon</span> <span style=\"background: rgba(0, 255, 0, 0.002405)\">quite</span> <span style=\"background: rgba(0, 255, 0, 0.010787)\">thing</span> <span style=\"background: rgba(0, 255, 0, 0.000797)\">arriving</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001516);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000699)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.001052)\">lunar</span> <span style=\"background: rgba(0, 255, 0, 0.001337)\">moment</span> <span style=\"background: rgba(0, 255, 0, 0.001516)\">engine</span> <span style=\"background: rgba(0, 255, 0, 0.000886)\">stops</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000690);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000424)\">getting</span> <span style=\"background: rgba(0, 255, 0, 0.000406)\">takes</span> <span style=\"background: rgba(0, 255, 0, 0.000573)\">lot</span> <span style=\"background: rgba(0, 255, 0, 0.000568)\">built</span> <span style=\"background: rgba(0, 255, 0, 0.000428)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.000614)\">extra</span> <span style=\"background: rgba(0, 255, 0, 0.000690)\">hours</span> <span style=\"background: rgba(0, 255, 0, 0.000544)\">flight</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000572);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000112)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.000119)\">figured</span> <span style=\"background: rgba(0, 255, 0, 0.000205)\">wise</span> <span style=\"background: rgba(0, 255, 0, 0.000216)\">allow</span> <span style=\"background: rgba(0, 255, 0, 0.000408)\">time</span> <span style=\"background: rgba(0, 255, 0, 0.000351)\">rather</span> <span style=\"background: rgba(0, 255, 0, 0.000367)\">less</span> <span style=\"background: rgba(0, 255, 0, 0.000533)\">initial</span> <span style=\"background: rgba(0, 255, 0, 0.000572)\">activities</span> <span style=\"background: rgba(0, 255, 0, 0.000421)\">case</span> <span style=\"background: rgba(0, 255, 0, 0.000232)\">anything</span> <span style=\"background: rgba(0, 255, 0, 0.000283)\">gone</span> <span style=\"background: rgba(0, 255, 0, 0.000154)\">wrong</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.002127);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000036)\">according</span> <span style=\"background: rgba(0, 255, 0, 0.000051)\">supposed</span> <span style=\"background: rgba(0, 255, 0, 0.000099)\">eat</span> <span style=\"background: rgba(0, 255, 0, 0.000171)\">rest</span> <span style=\"background: rgba(0, 255, 0, 0.002127)\">sleep</span> <span style=\"background: rgba(0, 255, 0, 0.000319)\">seven</span> <span style=\"background: rgba(0, 255, 0, 0.000188)\">hours</span> <span style=\"background: rgba(0, 255, 0, 0.000099)\">arriving</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000717);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000474)\">already</span> <span style=\"background: rgba(0, 255, 0, 0.000517)\">worked</span> <span style=\"background: rgba(0, 255, 0, 0.000544)\">full</span> <span style=\"background: rgba(0, 255, 0, 0.000439)\">day</span> <span style=\"background: rgba(0, 255, 0, 0.000717)\">wanted</span> <span style=\"background: rgba(0, 255, 0, 0.000470)\">fresh</span> <span style=\"background: rgba(0, 255, 0, 0.000432)\">activity</span> <span>. </span><div> </div><div><b>Document 10 - Label: True News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000069);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">father</span> <span style=\"background: rgba(0, 255, 0, 0.000069)\">chelsea</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">husband</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">congressman</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">pled</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">guilty</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">fraud</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001203);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000073)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.001203)\">chelsea</span> <span style=\"background: rgba(0, 255, 0, 0.000261)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000206)\">daughter</span> <span style=\"background: rgba(0, 255, 0, 0.000168)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.000113)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.000100)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.000088)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000090)\">secretary</span> <span style=\"background: rgba(0, 255, 0, 0.000095)\">state</span> <span style=\"background: rgba(0, 255, 0, 0.000082)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000109)\">recently</span> <span style=\"background: rgba(0, 255, 0, 0.000115)\">received</span> <span style=\"background: rgba(0, 255, 0, 0.000098)\">masters</span> <span style=\"background: rgba(0, 255, 0, 0.000067)\">degree</span> <span style=\"background: rgba(0, 255, 0, 0.000072)\">columbia</span> <span style=\"background: rgba(0, 255, 0, 0.000069)\">universitys</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">joseph</span> <span style=\"background: rgba(0, 255, 0, 0.000037)\">mailman</span> <span style=\"background: rgba(0, 255, 0, 0.000058)\">school</span> <span style=\"background: rgba(0, 255, 0, 0.000036)\">public</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">married</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">marc</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">investment</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001491);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000112)\">nuptials</span> <span style=\"background: rgba(0, 255, 0, 0.000208)\">ordinary</span> <span style=\"background: rgba(0, 255, 0, 0.000316)\">event</span> <span style=\"background: rgba(0, 255, 0, 0.000493)\">widely</span> <span style=\"background: rgba(0, 255, 0, 0.000483)\">covered</span> <span style=\"background: rgba(0, 255, 0, 0.000619)\">international</span> <span style=\"background: rgba(0, 255, 0, 0.000616)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.000668)\">media</span> <span style=\"background: rgba(0, 255, 0, 0.000818)\">brides</span> <span style=\"background: rgba(0, 255, 0, 0.000979)\">parents</span> <span style=\"background: rgba(0, 255, 0, 0.001484)\">two</span> <span style=\"background: rgba(0, 255, 0, 0.001284)\">prominent</span> <span style=\"background: rgba(0, 255, 0, 0.001491)\">politicians</span> <span style=\"background: rgba(0, 255, 0, 0.000861)\">recent</span> <span style=\"background: rgba(0, 255, 0, 0.000819)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.000590)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.000542)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.000453)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000427)\">secretary</span> <span style=\"background: rgba(0, 255, 0, 0.000378)\">state</span> <span style=\"background: rgba(0, 255, 0, 0.000245)\">hillary</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.024420);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000228)\">less</span> <span style=\"background: rgba(0, 255, 0, 0.000414)\">known</span> <span style=\"background: rgba(0, 255, 0, 0.000623)\">general</span> <span style=\"background: rgba(0, 255, 0, 0.000968)\">public</span> <span style=\"background: rgba(0, 255, 0, 0.001373)\">fact</span> <span style=\"background: rgba(0, 255, 0, 0.017387)\">grooms</span> <span style=\"background: rgba(0, 255, 0, 0.004225)\">parents</span> <span style=\"background: rgba(0, 255, 0, 0.003360)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.003726)\">politicians</span> <span style=\"background: rgba(0, 255, 0, 0.002715)\">federal</span> <span style=\"background: rgba(0, 255, 0, 0.002944)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.003144)\">congressman</span> <span style=\"background: rgba(0, 255, 0, 0.003594)\">edward</span> <span style=\"background: rgba(0, 255, 0, 0.024420)\">mezvinsky</span> <span style=\"background: rgba(0, 255, 0, 0.007974)\">iowa</span> <span style=\"background: rgba(0, 255, 0, 0.004664)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.004148)\">congresswoman</span> <span style=\"background: rgba(0, 255, 0, 0.011711)\">marjorie</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.068449);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000718)\">houston</span> <span style=\"background: rgba(0, 255, 0, 0.000595)\">chronicle</span> <span style=\"background: rgba(0, 255, 0, 0.001099)\">lives</span> <span style=\"background: rgba(0, 255, 0, 0.002469)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.043655)\">mezvinsky</span> <span style=\"background: rgba(0, 255, 0, 0.012614)\">parents</span> <span style=\"background: rgba(0, 255, 0, 0.013232)\">personally</span> <span style=\"background: rgba(0, 255, 0, 0.015400)\">long</span> <span style=\"background: rgba(0, 255, 0, 0.050739)\">chelsea</span> <span style=\"background: rgba(0, 255, 0, 0.018824)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.017094)\">marc</span> <span style=\"background: rgba(0, 255, 0, 0.068449)\">mezvinsky</span> <span style=\"background: rgba(0, 255, 0, 0.017991)\">announced</span> <span style=\"background: rgba(0, 255, 0, 0.012738)\">engagement</span> <span style=\"background: rgba(0, 255, 0, 0.015744)\">november</span> <span style=\"background: rgba(0, 255, 0, 0.055339)\">links</span> <span style=\"background: rgba(0, 255, 0, 0.008565)\">decidedly</span> <span style=\"background: rgba(0, 255, 0, 0.004894)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.002773)\">mezvinskys</span> <span style=\"background: rgba(0, 255, 0, 0.002161)\">long</span> <span style=\"background: rgba(0, 255, 0, 0.001277)\">political</span> <span style=\"background: rgba(0, 255, 0, 0.000702)\">allies</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.118484);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000623)\">freshman</span> <span style=\"background: rgba(0, 255, 0, 0.001272)\">cast</span> <span style=\"background: rgba(0, 255, 0, 0.001790)\">vote</span> <span style=\"background: rgba(0, 255, 0, 0.001891)\">got</span> <span style=\"background: rgba(0, 255, 0, 0.002273)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.003110)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.004450)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.006319)\">controversial</span> <span style=\"background: rgba(0, 255, 0, 0.008767)\">tax</span> <span style=\"background: rgba(0, 255, 0, 0.118484)\">package</span> <span style=\"background: rgba(0, 255, 0, 0.008585)\">house</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.039744);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.017874)\">earned</span> <span style=\"background: rgba(0, 255, 0, 0.025509)\">honored</span> <span style=\"background: rgba(0, 255, 0, 0.039744)\">place</span> <span style=\"background: rgba(0, 255, 0, 0.028941)\">vote</span> <span style=\"background: rgba(0, 255, 0, 0.024055)\">shouldnt</span> <span style=\"background: rgba(0, 255, 0, 0.014703)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.011842)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.008372)\">wrote</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.090478);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000810)\">darker</span> <span style=\"background: rgba(0, 255, 0, 0.001334)\">federal</span> <span style=\"background: rgba(0, 255, 0, 0.001659)\">prosecutors</span> <span style=\"background: rgba(0, 255, 0, 0.003181)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.003796)\">ed</span> <span style=\"background: rgba(0, 255, 0, 0.090478)\">mezvinsky</span> <span style=\"background: rgba(0, 255, 0, 0.014925)\">habitually</span> <span style=\"background: rgba(0, 255, 0, 0.008522)\">dropped</span> <span style=\"background: rgba(0, 255, 0, 0.006087)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.004755)\">names</span> <span style=\"background: rgba(0, 255, 0, 0.003443)\">boasted</span> <span style=\"background: rgba(0, 255, 0, 0.001660)\">defrauded</span> <span style=\"background: rgba(0, 255, 0, 0.001755)\">family</span> <span style=\"background: rgba(0, 255, 0, 0.001165)\">members</span> <span style=\"background: rgba(0, 255, 0, 0.000652)\">institutions</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.121293);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002829)\">ed</span> <span style=\"background: rgba(0, 255, 0, 0.121293)\">mezvinsky</span> <span style=\"background: rgba(0, 255, 0, 0.023037)\">sentenced</span> <span style=\"background: rgba(0, 255, 0, 0.019586)\">serve</span> <span style=\"background: rgba(0, 255, 0, 0.015279)\">months</span> <span style=\"background: rgba(0, 255, 0, 0.016675)\">federal</span> <span style=\"background: rgba(0, 255, 0, 0.018543)\">prison</span> <span style=\"background: rgba(0, 255, 0, 0.070820)\">pleading</span> <span style=\"background: rgba(0, 255, 0, 0.008815)\">guilty</span> <span style=\"background: rgba(0, 255, 0, 0.004833)\">massive</span> <span style=\"background: rgba(0, 255, 0, 0.004242)\">fraud</span> <span style=\"background: rgba(0, 255, 0, 0.002232)\">prosecutors</span> <span style=\"background: rgba(0, 255, 0, 0.002208)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.001872)\">amounted</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.018930);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.013598)\">released</span> <span style=\"background: rgba(0, 255, 0, 0.017170)\">custody</span> <span style=\"background: rgba(0, 255, 0, 0.018930)\">april</span> <span style=\"background: rgba(0, 255, 0, 0.016666)\">remains</span> <span style=\"background: rgba(0, 255, 0, 0.014287)\">federal</span> <span style=\"background: rgba(0, 255, 0, 0.011417)\">probation</span> <span>. </span><div> </div><div><b>Document 11 - Label: True News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000001);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">ad</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">class</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">assignment</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">kept</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000004);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">inspirational</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">tale</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">teacher</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">difference</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">unnecessary</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">explanatory</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">hundreds</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">sites</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">internet</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">widely</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">forwarded</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">good</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">luck</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">chain</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">letter</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">via</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000014);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">principles</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">fervently</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">wish</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">dedicated</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">make</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">lasting</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">difference</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">ones</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">world</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">better</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">place</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">hearts</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">reach</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000015);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">case</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">missed</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">end</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">paragraph</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">states</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000040);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">sister</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">helen</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">franciscan</span> <span style=\"background: rgba(0, 255, 0, 0.000026)\">submitted</span> <span style=\"background: rgba(0, 255, 0, 0.000028)\">good</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">things</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">journal</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">ideas</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">appeared</span> <span style=\"background: rgba(0, 255, 0, 0.000032)\">readers</span> <span style=\"background: rgba(0, 255, 0, 0.000040)\">digest</span> <span style=\"background: rgba(0, 255, 0, 0.000032)\">original</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">chicken</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">soup</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">soul</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">book</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">offered</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">yet</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">stories</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000957);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000050)\">sister</span> <span style=\"background: rgba(0, 255, 0, 0.000957)\">mrosla</span> <span style=\"background: rgba(0, 255, 0, 0.000232)\">first</span> <span style=\"background: rgba(0, 255, 0, 0.000141)\">met</span> <span style=\"background: rgba(0, 255, 0, 0.000130)\">mark</span> <span style=\"background: rgba(0, 255, 0, 0.000127)\">eklund</span> <span style=\"background: rgba(0, 255, 0, 0.000088)\">classroom</span> <span style=\"background: rgba(0, 255, 0, 0.000067)\">marys</span> <span style=\"background: rgba(0, 255, 0, 0.000096)\">school</span> <span style=\"background: rgba(0, 255, 0, 0.000075)\">encountered</span> <span style=\"background: rgba(0, 255, 0, 0.000060)\">served</span> <span style=\"background: rgba(0, 255, 0, 0.000044)\">junior</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">high</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">math</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001499);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000436)\">april</span> <span style=\"background: rgba(0, 255, 0, 0.000535)\">mark</span> <span style=\"background: rgba(0, 255, 0, 0.000758)\">sent</span> <span style=\"background: rgba(0, 255, 0, 0.000806)\">vietnam</span> <span style=\"background: rgba(0, 255, 0, 0.001472)\">assigned</span> <span style=\"background: rgba(0, 255, 0, 0.001382)\">transportation</span> <span style=\"background: rgba(0, 255, 0, 0.001357)\">company</span> <span style=\"background: rgba(0, 255, 0, 0.001499)\">phu</span> <span style=\"background: rgba(0, 255, 0, 0.001257)\">worked</span> <span style=\"background: rgba(0, 255, 0, 0.000880)\">truck</span> <span style=\"background: rgba(0, 255, 0, 0.000903)\">parts</span> <span style=\"background: rgba(0, 255, 0, 0.000697)\">kept</span> <span style=\"background: rgba(0, 255, 0, 0.000450)\">touch</span> <span style=\"background: rgba(0, 255, 0, 0.000485)\">family</span> <span style=\"background: rgba(0, 255, 0, 0.000267)\">friends</span> <span style=\"background: rgba(0, 255, 0, 0.000192)\">sister</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.008059);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000264)\">august</span> <span style=\"background: rgba(0, 255, 0, 0.000434)\">returning</span> <span style=\"background: rgba(0, 255, 0, 0.000577)\">sister</span> <span style=\"background: rgba(0, 255, 0, 0.008059)\">mrosla</span> <span style=\"background: rgba(0, 255, 0, 0.000849)\">learned</span> <span style=\"background: rgba(0, 255, 0, 0.000587)\">marks</span> <span style=\"background: rgba(0, 255, 0, 0.000253)\">death</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.020629);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000581)\">died</span> <span style=\"background: rgba(0, 255, 0, 0.000666)\">mark</span> <span style=\"background: rgba(0, 255, 0, 0.001050)\">eklund</span> <span style=\"background: rgba(0, 255, 0, 0.001397)\">killed</span> <span style=\"background: rgba(0, 255, 0, 0.001572)\">died</span> <span style=\"background: rgba(0, 255, 0, 0.020629)\">sleep</span> <span style=\"background: rgba(0, 255, 0, 0.002055)\">cerebral</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.076626);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004405)\">sister</span> <span style=\"background: rgba(0, 255, 0, 0.076626)\">mrosla</span> <span style=\"background: rgba(0, 255, 0, 0.020342)\">talked</span> <span style=\"background: rgba(0, 255, 0, 0.014587)\">associated</span> <span style=\"background: rgba(0, 255, 0, 0.011626)\">press</span> <span style=\"background: rgba(0, 255, 0, 0.011029)\">reporter</span> <span style=\"background: rgba(0, 255, 0, 0.008034)\">mark</span> <span style=\"background: rgba(0, 255, 0, 0.007724)\">letters</span> <span style=\"background: rgba(0, 255, 0, 0.006418)\">family</span> <span style=\"background: rgba(0, 255, 0, 0.003640)\">painted</span> <span style=\"background: rgba(0, 255, 0, 0.003930)\">safe</span> <span style=\"background: rgba(0, 255, 0, 0.004798)\">describing</span> <span style=\"background: rgba(0, 255, 0, 0.003592)\">work</span> <span style=\"background: rgba(0, 255, 0, 0.002906)\">clerk</span> <span style=\"background: rgba(0, 255, 0, 0.001579)\">truck</span> <span style=\"background: rgba(0, 255, 0, 0.001516)\">parts</span> <span style=\"background: rgba(0, 255, 0, 0.000897)\">depot</span> <span style=\"background: rgba(0, 255, 0, 0.000784)\">far</span> <span>. </span><div> </div><div><b>Document 12 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000015);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">plans</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">remove</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">offensive</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000043);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">pissed</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.000022)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">southern</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">conservative</span> <span style=\"background: rgba(0, 255, 0, 0.000033)\">daily</span> <span style=\"background: rgba(0, 255, 0, 0.000043)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">brief</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">post</span> <span style=\"background: rgba(0, 255, 0, 0.000026)\">reporting</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.000028)\">planned</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">remove</span> <span style=\"background: rgba(0, 255, 0, 0.000033)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">offensive</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.005457);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002418)\">although</span> <span style=\"background: rgba(0, 255, 0, 0.000449)\">headline</span> <span style=\"background: rgba(0, 255, 0, 0.000350)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.000254)\">stated</span> <span style=\"background: rgba(0, 255, 0, 0.000283)\">body</span> <span style=\"background: rgba(0, 255, 0, 0.000214)\">read</span> <span style=\"background: rgba(0, 255, 0, 0.000151)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.000138)\">barack</span> <span style=\"background: rgba(0, 255, 0, 0.000116)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.000092)\">warned</span> <span style=\"background: rgba(0, 255, 0, 0.000121)\">late</span> <span style=\"background: rgba(0, 255, 0, 0.000127)\">monday</span> <span style=\"background: rgba(0, 255, 0, 0.000118)\">afternoon</span> <span style=\"background: rgba(0, 255, 0, 0.000147)\">house</span> <span style=\"background: rgba(0, 255, 0, 0.000213)\">representatives</span> <span style=\"background: rgba(0, 255, 0, 0.000170)\">agree</span> <span style=\"background: rgba(0, 255, 0, 0.000249)\">continuing</span> <span style=\"background: rgba(0, 255, 0, 0.000256)\">resolution</span> <span style=\"background: rgba(0, 255, 0, 0.000376)\">fund</span> <span style=\"background: rgba(0, 255, 0, 0.000389)\">government</span> <span style=\"background: rgba(0, 255, 0, 0.000595)\">midnight</span> <span style=\"background: rgba(0, 255, 0, 0.005457)\">curtail</span> <span style=\"background: rgba(0, 255, 0, 0.001151)\">implementation</span> <span style=\"background: rgba(0, 255, 0, 0.000946)\">obamacare</span> <span style=\"background: rgba(0, 255, 0, 0.000533)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.000278)\">therefore</span> <span style=\"background: rgba(0, 255, 0, 0.000206)\">agree</span> <span style=\"background: rgba(0, 255, 0, 0.000158)\">sign</span> <span style=\"background: rgba(0, 255, 0, 0.000183)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.000078)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.000092)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.000055)\">immediately</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.002850);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000838)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.001147)\">clip</span> <span style=\"background: rgba(0, 255, 0, 0.000976)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.001438)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.001877)\">talking</span> <span style=\"background: rgba(0, 255, 0, 0.002726)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.001390)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.001330)\">attached</span> <span style=\"background: rgba(0, 255, 0, 0.001239)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.001443)\">mention</span> <span style=\"background: rgba(0, 255, 0, 0.001453)\">removing</span> <span style=\"background: rgba(0, 255, 0, 0.001076)\">landmark</span> <span style=\"background: rgba(0, 255, 0, 0.001030)\">describe</span> <span style=\"background: rgba(0, 255, 0, 0.001218)\">offensive</span> <span style=\"background: rgba(0, 255, 0, 0.001817)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.001590)\">explain</span> <span style=\"background: rgba(0, 255, 0, 0.001917)\">exactly</span> <span style=\"background: rgba(0, 255, 0, 0.002850)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.001599)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.001683)\">might</span> <span style=\"background: rgba(0, 255, 0, 0.001649)\">offend</span> <span style=\"background: rgba(0, 255, 0, 0.001320)\">rumor</span> <span style=\"background: rgba(0, 255, 0, 0.001804)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.001537)\">face</span> <span style=\"background: rgba(0, 255, 0, 0.001526)\">value</span> <span style=\"background: rgba(0, 255, 0, 0.001677)\">many</span> <span style=\"background: rgba(0, 255, 0, 0.001151)\">social</span> <span style=\"background: rgba(0, 255, 0, 0.000942)\">media</span> <span style=\"background: rgba(0, 255, 0, 0.000957)\">users</span> <span style=\"background: rgba(0, 255, 0, 0.000952)\">despite</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.003375);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000577)\">needless</span> <span style=\"background: rgba(0, 255, 0, 0.000795)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.001020)\">reports</span> <span style=\"background: rgba(0, 255, 0, 0.001284)\">suggested</span> <span style=\"background: rgba(0, 255, 0, 0.001191)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.001617)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.002009)\">designs</span> <span style=\"background: rgba(0, 255, 0, 0.001768)\">anything</span> <span style=\"background: rgba(0, 255, 0, 0.003375)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.001768)\">much</span> <span style=\"background: rgba(0, 255, 0, 0.001575)\">less</span> <span style=\"background: rgba(0, 255, 0, 0.001185)\">plans</span> <span style=\"background: rgba(0, 255, 0, 0.001056)\">close</span> <span style=\"background: rgba(0, 255, 0, 0.000998)\">remove</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.004916);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000638)\">rumor</span> <span style=\"background: rgba(0, 255, 0, 0.000962)\">wasnt</span> <span style=\"background: rgba(0, 255, 0, 0.001747)\">new</span> <span style=\"background: rgba(0, 255, 0, 0.003160)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.002400)\">months</span> <span style=\"background: rgba(0, 255, 0, 0.002699)\">earlier</span> <span style=\"background: rgba(0, 255, 0, 0.003454)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.004033)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.004916)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.003892)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.003531)\">verbatim</span> <span style=\"background: rgba(0, 255, 0, 0.002589)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.002396)\">asserted</span> <span style=\"background: rgba(0, 255, 0, 0.002176)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.002617)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.001110)\">claim</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.152275);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000784)\">turned</span> <span style=\"background: rgba(0, 255, 0, 0.001537)\">sentence</span> <span style=\"background: rgba(0, 255, 0, 0.003352)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.006699)\">september</span> <span style=\"background: rgba(0, 255, 0, 0.075061)\">cnsnews</span> <span style=\"background: rgba(0, 255, 0, 0.011727)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.008485)\">misleadingly</span> <span style=\"background: rgba(0, 255, 0, 0.005879)\">presented</span> <span style=\"background: rgba(0, 255, 0, 0.004449)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.004149)\">obamas</span> <span style=\"background: rgba(0, 255, 0, 0.003940)\">comments</span> <span style=\"background: rgba(0, 255, 0, 0.002373)\">looming</span> <span style=\"background: rgba(0, 255, 0, 0.002500)\">government</span> <span style=\"background: rgba(0, 255, 0, 0.002631)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.002652)\">barack</span> <span style=\"background: rgba(0, 255, 0, 0.002428)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.002067)\">warned</span> <span style=\"background: rgba(0, 255, 0, 0.002882)\">late</span> <span style=\"background: rgba(0, 255, 0, 0.003164)\">monday</span> <span style=\"background: rgba(0, 255, 0, 0.003030)\">afternoon</span> <span style=\"background: rgba(0, 255, 0, 0.003864)\">house</span> <span style=\"background: rgba(0, 255, 0, 0.005699)\">representatives</span> <span style=\"background: rgba(0, 255, 0, 0.004611)\">agree</span> <span style=\"background: rgba(0, 255, 0, 0.006810)\">continuing</span> <span style=\"background: rgba(0, 255, 0, 0.007057)\">resolution</span> <span style=\"background: rgba(0, 255, 0, 0.010400)\">fund</span> <span style=\"background: rgba(0, 255, 0, 0.010779)\">government</span> <span style=\"background: rgba(0, 255, 0, 0.016530)\">midnight</span> <span style=\"background: rgba(0, 255, 0, 0.152275)\">curtail</span> <span style=\"background: rgba(0, 255, 0, 0.032152)\">implementation</span> <span style=\"background: rgba(0, 255, 0, 0.026442)\">obamacare</span> <span style=\"background: rgba(0, 255, 0, 0.014899)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.007759)\">therefore</span> <span style=\"background: rgba(0, 255, 0, 0.005765)\">agree</span> <span style=\"background: rgba(0, 255, 0, 0.004422)\">sign</span> <span style=\"background: rgba(0, 255, 0, 0.005094)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.002187)\">liberty</span> <span style=\"background: rgba(0, 255, 0, 0.002573)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.001546)\">immediately</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.499500);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.008460)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.015207)\">conceded</span> <span style=\"background: rgba(0, 255, 0, 0.028719)\">even</span> <span style=\"background: rgba(0, 255, 0, 0.026057)\">house</span> <span style=\"background: rgba(0, 255, 0, 0.046828)\">refused</span> <span style=\"background: rgba(0, 255, 0, 0.048650)\">pass</span> <span style=\"background: rgba(0, 255, 0, 0.499500)\">cr</span> <span style=\"background: rgba(0, 255, 0, 0.098109)\">allowed</span> <span style=\"background: rgba(0, 255, 0, 0.050575)\">move</span> <span style=\"background: rgba(0, 255, 0, 0.040034)\">forward</span> <span style=\"background: rgba(0, 255, 0, 0.017919)\">major</span> <span style=\"background: rgba(0, 255, 0, 0.013492)\">government</span> <span style=\"background: rgba(0, 255, 0, 0.012638)\">programs</span> <span style=\"background: rgba(0, 255, 0, 0.012312)\">would</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.887190);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.036759)\">social</span> <span style=\"background: rgba(0, 255, 0, 0.887190)\">security</span> <span style=\"background: rgba(0, 255, 0, 0.203289)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.109180)\">go</span> <span style=\"background: rgba(0, 255, 0, 0.076331)\">troops</span> <span style=\"background: rgba(0, 255, 0, 0.054683)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.024867)\">remain</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.272960);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.035362)\">linked</span> <span style=\"background: rgba(0, 255, 0, 0.062391)\">remarks</span> <span style=\"background: rgba(0, 255, 0, 0.094505)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.075789)\">president</span> <span style=\"background: rgba(0, 255, 0, 0.109048)\">obama</span> <span style=\"background: rgba(0, 255, 0, 0.141134)\">described</span> <span style=\"background: rgba(0, 255, 0, 0.139653)\">consequences</span> <span style=\"background: rgba(0, 255, 0, 0.129414)\">government</span> <span style=\"background: rgba(0, 255, 0, 0.180195)\">personal</span> <span style=\"background: rgba(0, 255, 0, 0.161867)\">plan</span> <span style=\"background: rgba(0, 255, 0, 0.200427)\">away</span> <span style=\"background: rgba(0, 255, 0, 0.272960)\">statue</span> <span style=\"background: rgba(0, 255, 0, 0.122825)\">regard</span> <span style=\"background: rgba(0, 255, 0, 0.143190)\">operations</span> <span style=\"background: rgba(0, 255, 0, 0.091622)\">youre</span> <span style=\"background: rgba(0, 255, 0, 0.069805)\">social</span> <span style=\"background: rgba(0, 255, 0, 0.051724)\">keep</span> <span style=\"background: rgba(0, 255, 0, 0.048793)\">receiving</span> <span>. </span><div> </div><div><b>Document 13 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000019);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">teenaged</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">laura</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">bush</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">caused</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">classmate</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">automobile</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000018);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">driving</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">dangerous</span> <span style=\"background: rgba(0, 255, 0, 0.000016)\">activities</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">engage</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">us</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">every</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">little</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">realizing</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">peril</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000024);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">every</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">year</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">approximately</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">million</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">traffic</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">resulting</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000014);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">story</span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">one</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000020);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">resulted</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">someone</span> <span style=\"background: rgba(0, 255, 0, 0.000016)\">youve</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">never</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">heard</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">hands</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">someone</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000043);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000016)\">may</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">police</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">report</span> <span style=\"background: rgba(0, 255, 0, 0.000027)\">pertaining</span> <span style=\"background: rgba(0, 255, 0, 0.000027)\">fatal</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">accident</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.000043)\">place</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">near</span> <span style=\"background: rgba(0, 255, 0, 0.000024)\">made</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000051);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000044)\">contained</span> <span style=\"background: rgba(0, 255, 0, 0.000047)\">information</span> <span style=\"background: rgba(0, 255, 0, 0.000051)\">laura</span> <span style=\"background: rgba(0, 255, 0, 0.000047)\">welch</span> <span style=\"background: rgba(0, 255, 0, 0.000051)\">run</span> <span style=\"background: rgba(0, 255, 0, 0.000046)\">stop</span> <span style=\"background: rgba(0, 255, 0, 0.000042)\">causing</span> <span style=\"background: rgba(0, 255, 0, 0.000034)\">death</span> <span style=\"background: rgba(0, 255, 0, 0.000040)\">sole</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">vehicle</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001589);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000014)\">according</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">future</span> <span style=\"background: rgba(0, 255, 0, 0.000034)\">first</span> <span style=\"background: rgba(0, 255, 0, 0.000040)\">lady</span> <span style=\"background: rgba(0, 255, 0, 0.000046)\">driving</span> <span style=\"background: rgba(0, 255, 0, 0.000058)\">sedan</span> <span style=\"background: rgba(0, 255, 0, 0.000070)\">local</span> <span style=\"background: rgba(0, 255, 0, 0.000058)\">theater</span> <span style=\"background: rgba(0, 255, 0, 0.000059)\">clear</span> <span style=\"background: rgba(0, 255, 0, 0.000093)\">night</span> <span style=\"background: rgba(0, 255, 0, 0.000075)\">shortly</span> <span style=\"background: rgba(0, 255, 0, 0.000094)\">november</span> <span style=\"background: rgba(0, 255, 0, 0.000124)\">entered</span> <span style=\"background: rgba(0, 255, 0, 0.000184)\">intersection</span> <span style=\"background: rgba(0, 255, 0, 0.000236)\">without</span> <span style=\"background: rgba(0, 255, 0, 0.001589)\">heeding</span> <span style=\"background: rgba(0, 255, 0, 0.000529)\">stop</span> <span style=\"background: rgba(0, 255, 0, 0.000394)\">sign</span> <span style=\"background: rgba(0, 255, 0, 0.001474)\">collided</span> <span style=\"background: rgba(0, 255, 0, 0.000170)\">corvair</span> <span style=\"background: rgba(0, 255, 0, 0.000099)\">sedan</span> <span style=\"background: rgba(0, 255, 0, 0.000043)\">driven</span> <span style=\"background: rgba(0, 255, 0, 0.000021)\">michael</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.002250);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000028)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.000050)\">car</span> <span style=\"background: rgba(0, 255, 0, 0.000094)\">laura</span> <span style=\"background: rgba(0, 255, 0, 0.000121)\">welch</span> <span style=\"background: rgba(0, 255, 0, 0.002250)\">judy</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000584);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000584)\">fast</span> <span style=\"background: rgba(0, 255, 0, 0.000473)\">miss</span> <span style=\"background: rgba(0, 255, 0, 0.000386)\">welch</span> <span style=\"background: rgba(0, 255, 0, 0.000354)\">might</span> <span style=\"background: rgba(0, 255, 0, 0.000310)\">driving</span> <span style=\"background: rgba(0, 255, 0, 0.000302)\">open</span> <span>. </span><div> </div><div><b>Document 14 - Label: True News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000038);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">kissing</span> <span style=\"background: rgba(0, 255, 0, 0.000038)\">bugs</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">carry</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000016);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">barber</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">beetle</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">dangerous</span> <span style=\"background: rgba(0, 255, 0, 0.000016)\">even</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">causing</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">fatality</span> <span style=\"background: rgba(0, 255, 0, 0.000015)\">bite</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000012);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">looking</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">info</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">bug</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">named</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">barber</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000377);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">pink</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">penguin</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">website</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">states</span> <span style=\"background: rgba(0, 255, 0, 0.000006)\">bug</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">infect</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">parasite</span> <span style=\"background: rgba(0, 255, 0, 0.000012)\">parasite</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">carries</span> <span style=\"background: rgba(0, 255, 0, 0.000377)\">chagas</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000145);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000131)\">website</span> <span style=\"background: rgba(0, 255, 0, 0.000117)\">states</span> <span style=\"background: rgba(0, 255, 0, 0.000145)\">must</span> <span style=\"background: rgba(0, 255, 0, 0.000124)\">kill</span> <span style=\"background: rgba(0, 255, 0, 0.000107)\">bug</span> <span style=\"background: rgba(0, 255, 0, 0.000086)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.000077)\">need</span> <span style=\"background: rgba(0, 255, 0, 0.000070)\">call</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000080);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000065)\">sound</span> <span style=\"background: rgba(0, 255, 0, 0.000075)\">like</span> <span style=\"background: rgba(0, 255, 0, 0.000080)\">african</span> <span style=\"background: rgba(0, 255, 0, 0.000062)\">bug</span> <span style=\"background: rgba(0, 255, 0, 0.000056)\">nothing</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000070);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000029)\">several</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">friends</span> <span style=\"background: rgba(0, 255, 0, 0.000059)\">never</span> <span style=\"background: rgba(0, 255, 0, 0.000059)\">check</span> <span style=\"background: rgba(0, 255, 0, 0.000070)\">rely</span> <span style=\"background: rgba(0, 255, 0, 0.000044)\">site</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000041);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000041)\">thank</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000046);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000028)\">read</span> <span style=\"background: rgba(0, 255, 0, 0.000032)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.000035)\">bug</span> <span style=\"background: rgba(0, 255, 0, 0.000034)\">sounds</span> <span style=\"background: rgba(0, 255, 0, 0.000033)\">new</span> <span style=\"background: rgba(0, 255, 0, 0.000046)\">insect</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000042);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">aids</span> <span style=\"background: rgba(0, 255, 0, 0.000027)\">similar</span> <span style=\"background: rgba(0, 255, 0, 0.000023)\">disease</span> <span style=\"background: rgba(0, 255, 0, 0.000042)\">insect</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">supposedly</span> <span style=\"background: rgba(0, 255, 0, 0.000022)\">spreads</span> <span>. </span><div> </div><div><b>Document 15 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000355);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000262)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.000340)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.000319)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.000355)\">deport</span> <span style=\"background: rgba(0, 255, 0, 0.000262)\">nigerians</span> <span style=\"background: rgba(0, 255, 0, 0.000256)\">gets</span> <span style=\"background: rgba(0, 255, 0, 0.000242)\">elected</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.006750);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000539)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.000608)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.000950)\">quote</span> <span style=\"background: rgba(0, 255, 0, 0.000998)\">started</span> <span style=\"background: rgba(0, 255, 0, 0.001565)\">circulating</span> <span style=\"background: rgba(0, 255, 0, 0.001673)\">purportedly</span> <span style=\"background: rgba(0, 255, 0, 0.002299)\">uttered</span> <span style=\"background: rgba(0, 255, 0, 0.002642)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.003264)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.005124)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.006211)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.005835)\">deport</span> <span style=\"background: rgba(0, 255, 0, 0.005005)\">nigerians</span> <span style=\"background: rgba(0, 255, 0, 0.006684)\">american</span> <span style=\"background: rgba(0, 255, 0, 0.006750)\">billionaire</span> <span style=\"background: rgba(0, 255, 0, 0.004721)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.005000)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.006024)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.004799)\">shot</span> <span style=\"background: rgba(0, 255, 0, 0.003391)\">subtle</span> <span style=\"background: rgba(0, 255, 0, 0.003850)\">warning</span> <span style=\"background: rgba(0, 255, 0, 0.002904)\">nigerian</span> <span style=\"background: rgba(0, 255, 0, 0.003721)\">community</span> <span style=\"background: rgba(0, 255, 0, 0.003813)\">united</span> <span style=\"background: rgba(0, 255, 0, 0.003731)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.002656)\">nigerians</span> <span style=\"background: rgba(0, 255, 0, 0.003318)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.002717)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.001700)\">leave</span> <span style=\"background: rgba(0, 255, 0, 0.001325)\">country</span> <span style=\"background: rgba(0, 255, 0, 0.000656)\">becomes</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.004964);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004964)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.003593)\">threat</span> <span style=\"background: rgba(0, 255, 0, 0.003247)\">rally</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.101998);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002566)\">according</span> <span style=\"background: rgba(0, 255, 0, 0.004685)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.003622)\">nigerians</span> <span style=\"background: rgba(0, 255, 0, 0.005132)\">ad</span> <span style=\"background: rgba(0, 255, 0, 0.006782)\">mexicans</span> <span style=\"background: rgba(0, 255, 0, 0.009595)\">taken</span> <span style=\"background: rgba(0, 255, 0, 0.012388)\">jobs</span> <span style=\"background: rgba(0, 255, 0, 0.013116)\">meant</span> <span style=\"background: rgba(0, 255, 0, 0.014824)\">honest</span> <span style=\"background: rgba(0, 255, 0, 0.101998)\">hard</span> <span style=\"background: rgba(0, 255, 0, 0.010782)\">working</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.095852);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.082324)\">make</span> <span style=\"background: rgba(0, 255, 0, 0.081848)\">america</span> <span style=\"background: rgba(0, 255, 0, 0.068228)\">great</span> <span style=\"background: rgba(0, 255, 0, 0.061464)\">need</span> <span style=\"background: rgba(0, 255, 0, 0.052248)\">get</span> <span style=\"background: rgba(0, 255, 0, 0.095852)\">rid</span> <span style=\"background: rgba(0, 255, 0, 0.079913)\">mexicans</span> <span style=\"background: rgba(0, 255, 0, 0.056262)\">especially</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.048398)\">take</span> <span style=\"background: rgba(0, 255, 0, 0.055038)\">jobs</span> <span style=\"background: rgba(0, 255, 0, 0.074888)\">meant</span> <span style=\"background: rgba(0, 255, 0, 0.107449)\">honest</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">hard</span> <span style=\"background: rgba(0, 255, 0, 0.178888)\">working</span> <span style=\"background: rgba(0, 255, 0, 0.124745)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.111355)\">give</span> <span style=\"background: rgba(0, 255, 0, 0.063847)\">muslims</span> <span style=\"background: rgba(0, 255, 0, 0.047340)\">blow</span> <span style=\"background: rgba(0, 255, 0, 0.033093)\">us</span> <span style=\"background: rgba(0, 255, 0, 0.032277)\">trump</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.222259);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.220878)\">need</span> <span style=\"background: rgba(0, 255, 0, 0.199729)\">get</span> <span style=\"background: rgba(0, 255, 0, 0.222259)\">africans</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.114112);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.114112)\">especially</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.069640);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.069640)\">theyre</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.072017);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.055706)\">went</span> <span style=\"background: rgba(0, 255, 0, 0.047828)\">rally</span> <span style=\"background: rgba(0, 255, 0, 0.038464)\">alaska</span> <span style=\"background: rgba(0, 255, 0, 0.041343)\">met</span> <span style=\"background: rgba(0, 255, 0, 0.062013)\">one</span> <span style=\"background: rgba(0, 255, 0, 0.070193)\">african</span> <span style=\"background: rgba(0, 255, 0, 0.072017)\">entire</span> <span>. </span><div> </div><div><b>Document 16 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000030);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">senator</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">ted</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">cruz</span> <span style=\"background: rgba(0, 255, 0, 0.000026)\">scheduled</span> <span style=\"background: rgba(0, 255, 0, 0.000025)\">speak</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">democratic</span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">national</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000277);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000045)\">july</span> <span style=\"background: rgba(0, 255, 0, 0.000063)\">adobo</span> <span style=\"background: rgba(0, 255, 0, 0.000053)\">chronicle</span> <span style=\"background: rgba(0, 255, 0, 0.000093)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.000123)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.000171)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.000161)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.000168)\">reporting</span> <span style=\"background: rgba(0, 255, 0, 0.000161)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.000232)\">senator</span> <span style=\"background: rgba(0, 255, 0, 0.000146)\">ted</span> <span style=\"background: rgba(0, 255, 0, 0.000276)\">cruz</span> <span style=\"background: rgba(0, 255, 0, 0.000277)\">made</span> <span style=\"background: rgba(0, 255, 0, 0.000211)\">headlines</span> <span style=\"background: rgba(0, 255, 0, 0.000260)\">refusing</span> <span style=\"background: rgba(0, 255, 0, 0.000106)\">endorse</span> <span style=\"background: rgba(0, 255, 0, 0.000176)\">gop</span> <span style=\"background: rgba(0, 255, 0, 0.000169)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.000190)\">nominee</span> <span style=\"background: rgba(0, 255, 0, 0.000199)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.000205)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.000156)\">partys</span> <span style=\"background: rgba(0, 255, 0, 0.000135)\">national</span> <span style=\"background: rgba(0, 255, 0, 0.000080)\">agreed</span> <span style=\"background: rgba(0, 255, 0, 0.000083)\">speak</span> <span style=\"background: rgba(0, 255, 0, 0.000071)\">democratic</span> <span style=\"background: rgba(0, 255, 0, 0.000086)\">national</span> <span style=\"background: rgba(0, 255, 0, 0.000062)\">sources</span> <span style=\"background: rgba(0, 255, 0, 0.000068)\">close</span> <span style=\"background: rgba(0, 255, 0, 0.000067)\">democratic</span> <span style=\"background: rgba(0, 255, 0, 0.000084)\">national</span> <span style=\"background: rgba(0, 255, 0, 0.000059)\">committee</span> <span style=\"background: rgba(0, 255, 0, 0.000103)\">confirmed</span> <span style=\"background: rgba(0, 255, 0, 0.000085)\">tothe</span> <span style=\"background: rgba(0, 255, 0, 0.000110)\">adobo</span> <span style=\"background: rgba(0, 255, 0, 0.000093)\">chosen</span> <span style=\"background: rgba(0, 255, 0, 0.000059)\">theme</span> <span style=\"background: rgba(0, 255, 0, 0.000051)\">years</span> <span style=\"background: rgba(0, 255, 0, 0.000030)\">convention</span> <span style=\"background: rgba(0, 255, 0, 0.000031)\">vote</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000725);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000180)\">theme</span> <span style=\"background: rgba(0, 255, 0, 0.000310)\">reinforces</span> <span style=\"background: rgba(0, 255, 0, 0.000561)\">idea</span> <span style=\"background: rgba(0, 255, 0, 0.000725)\">american</span> <span style=\"background: rgba(0, 255, 0, 0.000553)\">vote</span> <span style=\"background: rgba(0, 255, 0, 0.000467)\">donald</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.046061);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001537)\">better</span> <span style=\"background: rgba(0, 255, 0, 0.002141)\">person</span> <span style=\"background: rgba(0, 255, 0, 0.046061)\">expound</span> <span style=\"background: rgba(0, 255, 0, 0.006172)\">theme</span> <span style=\"background: rgba(0, 255, 0, 0.004269)\">former</span> <span style=\"background: rgba(0, 255, 0, 0.002244)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.001704)\">presidential</span> <span style=\"background: rgba(0, 255, 0, 0.001397)\">candidate</span> <span style=\"background: rgba(0, 255, 0, 0.001126)\">senator</span> <span style=\"background: rgba(0, 255, 0, 0.000431)\">ted</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.136453);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002979)\">cruz</span> <span style=\"background: rgba(0, 255, 0, 0.004183)\">emphasized</span> <span style=\"background: rgba(0, 255, 0, 0.003163)\">theme</span> <span style=\"background: rgba(0, 255, 0, 0.004601)\">speech</span> <span style=\"background: rgba(0, 255, 0, 0.004902)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.006859)\">national</span> <span style=\"background: rgba(0, 255, 0, 0.006040)\">convention</span> <span style=\"background: rgba(0, 255, 0, 0.136453)\">cleveland</span> <span style=\"background: rgba(0, 255, 0, 0.010511)\">earlier</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.087131);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.059049)\">invited</span> <span style=\"background: rgba(0, 255, 0, 0.087131)\">dnc</span> <span style=\"background: rgba(0, 255, 0, 0.079237)\">speak</span> <span style=\"background: rgba(0, 255, 0, 0.073649)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.083838)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.077213)\">delivers</span> <span style=\"background: rgba(0, 255, 0, 0.083728)\">nomination</span> <span style=\"background: rgba(0, 255, 0, 0.065123)\">acceptance</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.407115);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.407115)\">although</span> <span style=\"background: rgba(0, 255, 0, 0.064755)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.051634)\">nothing</span> <span style=\"background: rgba(0, 255, 0, 0.044703)\">another</span> <span style=\"background: rgba(0, 255, 0, 0.046775)\">clickbait</span> <span style=\"background: rgba(0, 255, 0, 0.025830)\">fabrication</span> <span style=\"background: rgba(0, 255, 0, 0.021763)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.020098)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.017554)\">gained</span> <span style=\"background: rgba(0, 255, 0, 0.017189)\">traction</span> <span style=\"background: rgba(0, 255, 0, 0.013454)\">circulated</span> <span style=\"background: rgba(0, 255, 0, 0.018667)\">simultaneously</span> <span style=\"background: rgba(0, 255, 0, 0.011969)\">withanother</span> <span style=\"background: rgba(0, 255, 0, 0.008501)\">rumor</span> <span style=\"background: rgba(0, 255, 0, 0.008382)\">holding</span> <span style=\"background: rgba(0, 255, 0, 0.005567)\">democrats</span> <span style=\"background: rgba(0, 255, 0, 0.009465)\">take</span> <span style=\"background: rgba(0, 255, 0, 0.003963)\">republican</span> <span style=\"background: rgba(0, 255, 0, 0.003319)\">presidential</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.652683);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.010971)\">confusing</span> <span style=\"background: rgba(0, 255, 0, 0.031787)\">issue</span> <span style=\"background: rgba(0, 255, 0, 0.045424)\">adobo</span> <span style=\"background: rgba(0, 255, 0, 0.652683)\">chronicles</span> <span style=\"background: rgba(0, 255, 0, 0.069607)\">new</span> <span style=\"background: rgba(0, 255, 0, 0.043983)\">misinformation</span> <span style=\"background: rgba(0, 255, 0, 0.029822)\">method</span> <span style=\"background: rgba(0, 255, 0, 0.017477)\">facts</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 1.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004681)\">practice</span> <span style=\"background: rgba(0, 255, 0, 0.008102)\">noted</span> <span style=\"background: rgba(0, 255, 0, 0.009031)\">bottom</span> <span style=\"background: rgba(0, 255, 0, 0.011628)\">nearly</span> <span style=\"background: rgba(0, 255, 0, 0.010993)\">unreadable</span> <span style=\"background: rgba(0, 255, 0, 0.007356)\">blowing</span> <span style=\"background: rgba(0, 255, 0, 0.007545)\">graphic</span> <span style=\"background: rgba(0, 255, 0, 0.006747)\">readable</span> <span style=\"background: rgba(0, 255, 0, 0.008673)\">size</span> <span style=\"background: rgba(0, 255, 0, 0.013999)\">reveals</span> <span style=\"background: rgba(0, 255, 0, 0.014767)\">legend</span> <span style=\"background: rgba(0, 255, 0, 0.014432)\">actually</span> <span style=\"background: rgba(0, 255, 0, 0.013391)\">addition</span> <span style=\"background: rgba(0, 255, 0, 0.016999)\">confusing</span> <span style=\"background: rgba(0, 255, 0, 0.027726)\">label</span> <span style=\"background: rgba(0, 255, 0, 0.032350)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.029839)\">bottom</span> <span style=\"background: rgba(0, 255, 0, 0.041737)\">adobo</span> <span style=\"background: rgba(0, 255, 0, 0.032575)\">chronicle</span> <span style=\"background: rgba(0, 255, 0, 0.045443)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.052682)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.086594)\">carries</span> <span style=\"background: rgba(0, 255, 0, 0.123790)\">adobo</span> <span style=\"background: rgba(0, 255, 0, 1.000000)\">chronicles</span> <span style=\"background: rgba(0, 255, 0, 0.076746)\">source</span> <span style=\"background: rgba(0, 255, 0, 0.050005)\">unbelievable</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.221152);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.132623)\">everything</span> <span style=\"background: rgba(0, 255, 0, 0.221152)\">read</span> <span style=\"background: rgba(0, 255, 0, 0.204908)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.179408)\">based</span> <span style=\"background: rgba(0, 255, 0, 0.185250)\">except</span> <span>. </span><div> </div><div><b>Document 17 - Label: Fake News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.002007);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000659)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000974)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.001387)\">suggested</span> <span style=\"background: rgba(0, 255, 0, 0.001578)\">speech</span> <span style=\"background: rgba(0, 255, 0, 0.002007)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.001908)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.001145)\">run</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.008537);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001381)\">october</span> <span style=\"background: rgba(0, 255, 0, 0.001820)\">entertainment</span> <span style=\"background: rgba(0, 255, 0, 0.002549)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.003457)\">sitethe</span> <span style=\"background: rgba(0, 255, 0, 0.003346)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.004112)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.005105)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.005222)\">reporting</span> <span style=\"background: rgba(0, 255, 0, 0.005162)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.005880)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.007061)\">said</span> <span style=\"background: rgba(0, 255, 0, 0.006993)\">speech</span> <span style=\"background: rgba(0, 255, 0, 0.008537)\">wanted</span> <span style=\"background: rgba(0, 255, 0, 0.006780)\">see</span> <span style=\"background: rgba(0, 255, 0, 0.006949)\">someone</span> <span style=\"background: rgba(0, 255, 0, 0.007675)\">like</span> <span style=\"background: rgba(0, 255, 0, 0.007153)\">donald</span> <span style=\"background: rgba(0, 255, 0, 0.005749)\">trump</span> <span style=\"background: rgba(0, 255, 0, 0.003146)\">run</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.014875);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001147)\">hybrid</span> <span style=\"background: rgba(0, 255, 0, 0.001795)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.002326)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.002502)\">publishes</span> <span style=\"background: rgba(0, 255, 0, 0.004599)\">mixture</span> <span style=\"background: rgba(0, 255, 0, 0.003433)\">real</span> <span style=\"background: rgba(0, 255, 0, 0.004498)\">fake</span> <span style=\"background: rgba(0, 255, 0, 0.004775)\">independent</span> <span style=\"background: rgba(0, 255, 0, 0.005683)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.008323)\">platform</span> <span style=\"background: rgba(0, 255, 0, 0.007354)\">allow</span> <span style=\"background: rgba(0, 255, 0, 0.012337)\">people</span> <span style=\"background: rgba(0, 255, 0, 0.009227)\">independent</span> <span style=\"background: rgba(0, 255, 0, 0.011926)\">journalist</span> <span style=\"background: rgba(0, 255, 0, 0.014875)\">bring</span> <span style=\"background: rgba(0, 255, 0, 0.007806)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.007995)\">directly</span> <span style=\"background: rgba(0, 255, 0, 0.006289)\">come</span> <span style=\"background: rgba(0, 255, 0, 0.005390)\">us</span> <span style=\"background: rgba(0, 255, 0, 0.003153)\">source</span> <span style=\"background: rgba(0, 255, 0, 0.003150)\">independent</span> <span style=\"background: rgba(0, 255, 0, 0.003035)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.003574)\">effected</span> <span style=\"background: rgba(0, 255, 0, 0.002436)\">big</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.011299);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.009830)\">hybrid</span> <span style=\"background: rgba(0, 255, 0, 0.011299)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.010662)\">news</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.010722);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.008023)\">part</span> <span style=\"background: rgba(0, 255, 0, 0.006354)\">stories</span> <span style=\"background: rgba(0, 255, 0, 0.010722)\">already</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.010164);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.010164)\">stories</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.065739);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.005967)\">news</span> <span style=\"background: rgba(0, 255, 0, 0.007931)\">portion</span> <span style=\"background: rgba(0, 255, 0, 0.012295)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.016497)\">speech</span> <span style=\"background: rgba(0, 255, 0, 0.019061)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.018477)\">purportedly</span> <span style=\"background: rgba(0, 255, 0, 0.022028)\">delivered</span> <span style=\"background: rgba(0, 255, 0, 0.026364)\">goldman</span> <span style=\"background: rgba(0, 255, 0, 0.035022)\">sachs</span> <span style=\"background: rgba(0, 255, 0, 0.041884)\">excerpt</span> <span style=\"background: rgba(0, 255, 0, 0.051230)\">speech</span> <span style=\"background: rgba(0, 255, 0, 0.063906)\">published</span> <span style=\"background: rgba(0, 255, 0, 0.050160)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.065739)\">campaign</span> <span style=\"background: rgba(0, 255, 0, 0.059654)\">refused</span> <span style=\"background: rgba(0, 255, 0, 0.034620)\">verify</span> <span style=\"background: rgba(0, 255, 0, 0.030420)\">male</span> <span style=\"background: rgba(0, 255, 0, 0.025411)\">question</span> <span style=\"background: rgba(0, 255, 0, 0.016205)\">risk</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.035385);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.019576)\">mike</span> <span style=\"background: rgba(0, 255, 0, 0.019050)\">bloomberg</span> <span style=\"background: rgba(0, 255, 0, 0.018576)\">billion</span> <span style=\"background: rgba(0, 255, 0, 0.018951)\">reasons</span> <span style=\"background: rgba(0, 255, 0, 0.035385)\">take</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.058442);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.020739)\">need</span> <span style=\"background: rgba(0, 255, 0, 0.027032)\">wholesale</span> <span style=\"background: rgba(0, 255, 0, 0.046894)\">change</span> <span style=\"background: rgba(0, 255, 0, 0.046243)\">washington</span> <span style=\"background: rgba(0, 255, 0, 0.058442)\">people</span> <span style=\"background: rgba(0, 255, 0, 0.039059)\">dont</span> <span style=\"background: rgba(0, 255, 0, 0.033944)\">need</span> <span style=\"background: rgba(0, 255, 0, 0.041996)\">job</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.039566);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.024928)\">secretary</span> <span style=\"background: rgba(0, 255, 0, 0.039566)\">thats</span> <span style=\"background: rgba(0, 255, 0, 0.029326)\">really</span> <span style=\"background: rgba(0, 255, 0, 0.019110)\">interesting</span> <span>. </span><div> </div><div><b>Document 18 - Label: True News - Predicted: Legitimate</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000005);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">page</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">campaign</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">web</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">site</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">campus</span> <span style=\"background: rgba(0, 255, 0, 0.000005)\">sexual</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">assault</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">edited</span> <span style=\"background: rgba(0, 255, 0, 0.000003)\">remove</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">wording</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000295);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">august</span> <span style=\"background: rgba(0, 255, 0, 0.000002)\">buzzfeedpublished</span> <span style=\"background: rgba(0, 255, 0, 0.000004)\">article</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">arkansas</span> <span style=\"background: rgba(0, 255, 0, 0.000007)\">resident</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">juanita</span> <span style=\"background: rgba(0, 255, 0, 0.000013)\">briefly</span> <span style=\"background: rgba(0, 255, 0, 0.000010)\">came</span> <span style=\"background: rgba(0, 255, 0, 0.000008)\">scrutiny</span> <span style=\"background: rgba(0, 255, 0, 0.000011)\">leaked</span> <span style=\"background: rgba(0, 255, 0, 0.000022)\">assertion</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">bill</span> <span style=\"background: rgba(0, 255, 0, 0.000017)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000022)\">serving</span> <span style=\"background: rgba(0, 255, 0, 0.000019)\">states</span> <span style=\"background: rgba(0, 255, 0, 0.000018)\">attorney</span> <span style=\"background: rgba(0, 255, 0, 0.000295)\">raped</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000333);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000135)\">broaddrick</span> <span style=\"background: rgba(0, 255, 0, 0.000183)\">didnt</span> <span style=\"background: rgba(0, 255, 0, 0.000205)\">speak</span> <span style=\"background: rgba(0, 255, 0, 0.000284)\">many</span> <span style=\"background: rgba(0, 255, 0, 0.000236)\">years</span> <span style=\"background: rgba(0, 255, 0, 0.000259)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000333)\">denied</span> <span style=\"background: rgba(0, 255, 0, 0.000265)\">sexually</span> <span style=\"background: rgba(0, 255, 0, 0.000208)\">assaulting</span> <span style=\"background: rgba(0, 255, 0, 0.000140)\">criminal</span> <span style=\"background: rgba(0, 255, 0, 0.000104)\">charges</span> <span style=\"background: rgba(0, 255, 0, 0.000095)\">ever</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000354);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000186)\">broaddrick</span> <span style=\"background: rgba(0, 255, 0, 0.000225)\">mostly</span> <span style=\"background: rgba(0, 255, 0, 0.000216)\">footnote</span> <span style=\"background: rgba(0, 255, 0, 0.000252)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.000354)\">monica</span> <span style=\"background: rgba(0, 255, 0, 0.000215)\">lewinsky</span> <span style=\"background: rgba(0, 255, 0, 0.000211)\">scandal</span> <span style=\"background: rgba(0, 255, 0, 0.000149)\">content</span> <span style=\"background: rgba(0, 255, 0, 0.000185)\">public</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.011287);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000176)\">juanita</span> <span style=\"background: rgba(0, 255, 0, 0.000241)\">broaddrick</span> <span style=\"background: rgba(0, 255, 0, 0.000355)\">placed</span> <span style=\"background: rgba(0, 255, 0, 0.000446)\">public</span> <span style=\"background: rgba(0, 255, 0, 0.000631)\">eye</span> <span style=\"background: rgba(0, 255, 0, 0.000581)\">part</span> <span style=\"background: rgba(0, 255, 0, 0.000701)\">september</span> <span style=\"background: rgba(0, 255, 0, 0.000584)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.000716)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.000915)\">posted</span> <span style=\"background: rgba(0, 255, 0, 0.000963)\">tweet</span> <span style=\"background: rgba(0, 255, 0, 0.000934)\">stating</span> <span style=\"background: rgba(0, 255, 0, 0.001493)\">every</span> <span style=\"background: rgba(0, 255, 0, 0.001128)\">survivor</span> <span style=\"background: rgba(0, 255, 0, 0.001096)\">sexual</span> <span style=\"background: rgba(0, 255, 0, 0.000983)\">assault</span> <span style=\"background: rgba(0, 255, 0, 0.001542)\">right</span> <span style=\"background: rgba(0, 255, 0, 0.001662)\">heard</span> <span style=\"background: rgba(0, 255, 0, 0.001842)\">right</span> <span style=\"background: rgba(0, 255, 0, 0.002205)\">every</span> <span style=\"background: rgba(0, 255, 0, 0.001709)\">survivor</span> <span style=\"background: rgba(0, 255, 0, 0.001748)\">sexual</span> <span style=\"background: rgba(0, 255, 0, 0.011287)\">assaultyou</span> <span style=\"background: rgba(0, 255, 0, 0.001367)\">right</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.004449);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.004449)\">right</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.021922);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.003627)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.005581)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.009018)\">clinton</span> <span style=\"background: rgba(0, 255, 0, 0.015817)\">september</span> <span style=\"background: rgba(0, 255, 0, 0.018874)\">tweet</span> <span style=\"background: rgba(0, 255, 0, 0.020521)\">eventually</span> <span style=\"background: rgba(0, 255, 0, 0.014123)\">came</span> <span style=\"background: rgba(0, 255, 0, 0.011574)\">broaddricks</span> <span style=\"background: rgba(0, 255, 0, 0.018818)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.018490)\">sent</span> <span style=\"background: rgba(0, 255, 0, 0.021922)\">would</span> <span style=\"background: rgba(0, 255, 0, 0.020174)\">become</span> <span style=\"background: rgba(0, 255, 0, 0.012650)\">widely</span> <span style=\"background: rgba(0, 255, 0, 0.008788)\">circulated</span> <span style=\"background: rgba(0, 255, 0, 0.007511)\">response</span> <span style=\"background: rgba(0, 255, 0, 0.006286)\">clintons</span> <span style=\"background: rgba(0, 255, 0, 0.005516)\">years</span> <span style=\"background: rgba(0, 255, 0, 0.004808)\">old</span> <span style=\"background: rgba(0, 255, 0, 0.002970)\">bill</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.143168);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002139)\">attorney</span> <span style=\"background: rgba(0, 255, 0, 0.004395)\">general</span> <span style=\"background: rgba(0, 255, 0, 0.143168)\">raped</span> <span style=\"background: rgba(0, 255, 0, 0.015725)\">hillary</span> <span style=\"background: rgba(0, 255, 0, 0.012064)\">tried</span> <span style=\"background: rgba(0, 255, 0, 0.004928)\">silence</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.054451);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.054451)\">never</span> <span style=\"background: rgba(0, 255, 0, 0.040239)\">goes</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.080468);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.045583)\">juanita</span> <span style=\"background: rgba(0, 255, 0, 0.055356)\">broaddrick</span> <span style=\"background: rgba(0, 255, 0, 0.080468)\">january</span> <span style=\"background: rgba(0, 255, 0, 0.070232)\">tense</span> <span style=\"background: rgba(0, 255, 0, 0.074416)\">election</span> <span style=\"background: rgba(0, 255, 0, 0.073816)\">tweet</span> <span style=\"background: rgba(0, 255, 0, 0.060966)\">slowly</span> <span style=\"background: rgba(0, 255, 0, 0.042558)\">gained</span> <span>. </span><div> </div><div><b>Document 19 - Label: True News - Predicted: Fake</b></div>\n",
    "<span style=\"background: rgba(255, 0, 0, 0.000000);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">discontinued</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">causing</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000009);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000009)\">hylands</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">stopped</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">distributing</span> <span style=\"background: rgba(0, 255, 0, 0.000001)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">products</span> <span style=\"background: rgba(0, 255, 0, 0.000000)\">united</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.001083);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000020)\">october</span> <span style=\"background: rgba(0, 255, 0, 0.000043)\">food</span> <span style=\"background: rgba(0, 255, 0, 0.000714)\">drug</span> <span style=\"background: rgba(0, 255, 0, 0.000246)\">administration</span> <span style=\"background: rgba(0, 255, 0, 0.000206)\">notified</span> <span style=\"background: rgba(0, 255, 0, 0.000315)\">consumers</span> <span style=\"background: rgba(0, 255, 0, 0.001083)\">hylands</span> <span style=\"background: rgba(0, 255, 0, 0.000495)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.000881)\">homeopathic</span> <span style=\"background: rgba(0, 255, 0, 0.000206)\">intended</span> <span style=\"background: rgba(0, 255, 0, 0.000129)\">provide</span> <span style=\"background: rgba(0, 255, 0, 0.000097)\">temporary</span> <span style=\"background: rgba(0, 255, 0, 0.000093)\">relief</span> <span style=\"background: rgba(0, 255, 0, 0.000066)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.000057)\">symptoms</span> <span style=\"background: rgba(0, 255, 0, 0.000060)\">recalled</span> <span style=\"background: rgba(0, 255, 0, 0.000032)\">agency</span> <span style=\"background: rgba(0, 255, 0, 0.000041)\">received</span> <span style=\"background: rgba(0, 255, 0, 0.000037)\">reports</span> <span style=\"background: rgba(0, 255, 0, 0.000046)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.000338)\">adverse</span> <span style=\"background: rgba(0, 255, 0, 0.000039)\">events</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000709);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000101)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.000126)\">stated</span> <span style=\"background: rgba(0, 255, 0, 0.000185)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.000381)\">contained</span> <span style=\"background: rgba(0, 255, 0, 0.000300)\">inconsistent</span> <span style=\"background: rgba(0, 255, 0, 0.000247)\">amounts</span> <span style=\"background: rgba(0, 255, 0, 0.000465)\">belladonna</span> <span style=\"background: rgba(0, 255, 0, 0.000535)\">could</span> <span style=\"background: rgba(0, 255, 0, 0.000683)\">pose</span> <span style=\"background: rgba(0, 255, 0, 0.000709)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.000640)\">risk</span> <span style=\"background: rgba(0, 255, 0, 0.000533)\">harm</span> <span style=\"background: rgba(0, 255, 0, 0.000488)\">children</span> <span style=\"background: rgba(0, 255, 0, 0.000597)\">including</span> <span style=\"background: rgba(0, 255, 0, 0.000391)\">warned</span> <span style=\"background: rgba(0, 255, 0, 0.000677)\">consumers</span> <span style=\"background: rgba(0, 255, 0, 0.000620)\">stop</span> <span style=\"background: rgba(0, 255, 0, 0.000558)\">using</span> <span style=\"background: rgba(0, 255, 0, 0.000337)\">discard</span> <span style=\"background: rgba(0, 255, 0, 0.000406)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.000344)\">manufactured</span> <span style=\"background: rgba(0, 255, 0, 0.000345)\">contain</span> <span style=\"background: rgba(0, 255, 0, 0.000527)\">small</span> <span style=\"background: rgba(0, 255, 0, 0.000385)\">amount</span> <span style=\"background: rgba(0, 255, 0, 0.000374)\">substance</span> <span style=\"background: rgba(0, 255, 0, 0.000273)\">cause</span> <span style=\"background: rgba(0, 255, 0, 0.000247)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.000156)\">harm</span> <span style=\"background: rgba(0, 255, 0, 0.000119)\">larger</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.000355);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000285)\">important</span> <span style=\"background: rgba(0, 255, 0, 0.000275)\">amount</span> <span style=\"background: rgba(0, 255, 0, 0.000355)\">belladonna</span> <span style=\"background: rgba(0, 255, 0, 0.000342)\">carefully</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.006890);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000234)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.006337)\">laboratory</span> <span style=\"background: rgba(0, 255, 0, 0.001984)\">analysis</span> <span style=\"background: rgba(0, 255, 0, 0.001656)\">found</span> <span style=\"background: rgba(0, 255, 0, 0.006890)\">hylands</span> <span style=\"background: rgba(0, 255, 0, 0.000846)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.000431)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.000212)\">contain</span> <span style=\"background: rgba(0, 255, 0, 0.000123)\">inconsistent</span> <span style=\"background: rgba(0, 255, 0, 0.000052)\">amounts</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.014705);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000241)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.000533)\">received</span> <span style=\"background: rgba(0, 255, 0, 0.000710)\">reports</span> <span style=\"background: rgba(0, 255, 0, 0.001188)\">serious</span> <span style=\"background: rgba(0, 255, 0, 0.014705)\">adverse</span> <span style=\"background: rgba(0, 255, 0, 0.002495)\">events</span> <span style=\"background: rgba(0, 255, 0, 0.001197)\">children</span> <span style=\"background: rgba(0, 255, 0, 0.000621)\">taking</span> <span style=\"background: rgba(0, 255, 0, 0.000502)\">product</span> <span style=\"background: rgba(0, 255, 0, 0.000331)\">consistent</span> <span style=\"background: rgba(0, 255, 0, 0.000248)\">belladonna</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.004322);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.001965)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.002535)\">also</span> <span style=\"background: rgba(0, 255, 0, 0.004322)\">received</span> <span style=\"background: rgba(0, 255, 0, 0.003722)\">reports</span> <span style=\"background: rgba(0, 255, 0, 0.003748)\">children</span> <span style=\"background: rgba(0, 255, 0, 0.003021)\">consumed</span> <span style=\"background: rgba(0, 255, 0, 0.002886)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.003110)\">child</span> <span style=\"background: rgba(0, 255, 0, 0.002876)\">resistant</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.018005);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.000635)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.018005)\">hylands</span> <span style=\"background: rgba(0, 255, 0, 0.002746)\">teething</span> <span style=\"background: rgba(0, 255, 0, 0.001810)\">tablets</span> <span style=\"background: rgba(0, 255, 0, 0.001187)\">safety</span> <span style=\"background: rgba(0, 255, 0, 0.001092)\">aware</span> <span style=\"background: rgba(0, 255, 0, 0.000712)\">proven</span> <span style=\"background: rgba(0, 255, 0, 0.000571)\">clinical</span> <span style=\"background: rgba(0, 255, 0, 0.000431)\">benefit</span> <span style=\"background: rgba(0, 255, 0, 0.000256)\">offered</span> <span>. </span><div> </div><span style=\"background: rgba(255, 0, 0, 0.006029);width: 10px;height: 10px;display:inline-block;\"></span> <span style=\"background: rgba(0, 255, 0, 0.002975)\">fda</span> <span style=\"background: rgba(0, 255, 0, 0.003192)\">recommends</span> <span style=\"background: rgba(0, 255, 0, 0.005030)\">consumers</span> <span style=\"background: rgba(0, 255, 0, 0.004740)\">use</span> <span style=\"background: rgba(0, 255, 0, 0.006029)\">product</span> <span style=\"background: rgba(0, 255, 0, 0.005146)\">dispose</span> <span>. </span><div> </div>\n",
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