05 Natural Language Processing with Disaster Tweets.ipynb

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   },
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.037061,
     "end_time": "2021-06-01T03:36:12.743416",
     "exception": false,
     "start_time": "2021-06-01T03:36:12.706355",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "![Unknown.png](attachment:22d596b3-5aa1-433d-81f4-e16d1ee27c29.png)\n",
    "\n",
    "# Natural Language Processing with Disaster Tweets\n",
    "\n",
    "## Overview\n",
    "\n",
    "This Notebook will be completed in two main ways.<br/>\n",
    "First, find and visualize useful data or meaningful relationships within the data.<br/>\n",
    "Second, select a model based on the visualization of the previous process. Transform or refine the data into the appropriate form for the model to be used.<br/><br/>\n",
    "\n",
    "This competition is about predicting positive and negative through data.<br/>\n",
    "That is why we need to go through a careful data preprocessing process.\n",
    "\n",
    "#### My opinion :\n",
    "To provide a variety of information to the deep learning model, we will combine the columns 'keyword', 'location' and 'text' of the data."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "***\n",
    "\n",
    "## My workflow\n",
    "#### 1. Import & Install libray\n",
    "* Import basic & Enginnering libray\n",
    "* Install pyspellchecker / stopwords list\n",
    "\n",
    "#### 2. Check out my data\n",
    "* Check Shape / Info\n",
    "\n",
    "#### 3. Exploratory Data Analysis(EDA) with Visualization [Before Preprocessing]\n",
    "* Plot the target data percent\n",
    "* Plot the Keyword per Count\n",
    "* Number of alphabets by sentence / Number of words by sentence\n",
    "\n",
    "#### 4. Prepocessing Data\n",
    "* Null value processing\n",
    "\n",
    "#### 5. Feature Enginnering \n",
    "* Text data to nomalization\n",
    "* Use SpellChecker libray\n",
    "* Plot WordClouds\n",
    "* Drop unuseful columns\n",
    "* Text data tokenization\n",
    "* Text data to fit on Glove Embedding\n",
    "\n",
    "#### 6. Modeling\n",
    "* Glove & LSTM Modeling\n",
    "* Training\n",
    "* Plot model's loss / accuray values\n",
    "\n",
    "#### 7. Submission\n",
    "* Submit the predictions"
   ]
  },
  {
   "cell_type": "markdown",
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    },
    "tags": []
   },
   "source": [
    "# 1. Import & Install libray\n",
    "* Import basic & Enginnering libray\n",
    "* Install pyspellchecker / stopwords list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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     "status": "completed"
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorflow Version 2.4.1\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from keras.preprocessing.text import Tokenizer\n",
    "from keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.layers import Conv1D, Bidirectional, LSTM, Dense, Input, Dropout\n",
    "from tensorflow.keras.layers import SpatialDropout1D, BatchNormalization\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ReduceLROnPlateau\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import os \n",
    "import re\n",
    "\n",
    "from nltk.stem import SnowballStemmer\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "\n",
    "\n",
    "from wordcloud import WordCloud\n",
    "from PIL import Image\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('seaborn')\n",
    "%matplotlib inline\n",
    "\n",
    "print(\"Tensorflow Version\",tf.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to /usr/share/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('stopwords')\n",
    "from nltk.corpus import stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:19.376502Z",
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     "shell.execute_reply.started": "2021-06-01T03:27:07.793673Z"
    },
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     "exception": false,
     "start_time": "2021-06-01T03:36:19.336370",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pyspellchecker\r\n",
      "  Downloading pyspellchecker-0.6.2-py3-none-any.whl (2.7 MB)\r\n",
      "\u001b[K     |████████████████████████████████| 2.7 MB 1.2 MB/s \r\n",
      "\u001b[?25hInstalling collected packages: pyspellchecker\r\n",
      "Successfully installed pyspellchecker-0.6.2\r\n",
      "\u001b[33mWARNING: You are using pip version 21.0.1; however, version 21.1.2 is available.\r\n",
      "You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install pyspellchecker\n",
    "from spellchecker import SpellChecker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>location</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Our Deeds are the Reason of this #earthquake M...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Forest fire near La Ronge Sask. Canada</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>All residents asked to 'shelter in place' are ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13,000 people receive #wildfires evacuation or...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Just got sent this photo from Ruby #Alaska as ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id keyword location                                               text  \\\n",
       "0   1     NaN      NaN  Our Deeds are the Reason of this #earthquake M...   \n",
       "1   4     NaN      NaN             Forest fire near La Ronge Sask. Canada   \n",
       "2   5     NaN      NaN  All residents asked to 'shelter in place' are ...   \n",
       "3   6     NaN      NaN  13,000 people receive #wildfires evacuation or...   \n",
       "4   7     NaN      NaN  Just got sent this photo from Ruby #Alaska as ...   \n",
       "\n",
       "   target  \n",
       "0       1  \n",
       "1       1  \n",
       "2       1  \n",
       "3       1  \n",
       "4       1  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('/kaggle/input/nlp-getting-started/train.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 2. Check out my data\n",
    "* Check Shape / Info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train data size : (7613, 5)\n"
     ]
    }
   ],
   "source": [
    "print(\"Train data size : {}\".format(df.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
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    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7613 entries, 0 to 7612\n",
      "Data columns (total 5 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   id        7613 non-null   int64 \n",
      " 1   keyword   7552 non-null   object\n",
      " 2   location  5080 non-null   object\n",
      " 3   text      7613 non-null   object\n",
      " 4   target    7613 non-null   int64 \n",
      "dtypes: int64(2), object(3)\n",
      "memory usage: 297.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
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    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x72 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "YlGnBu_palette = sns.color_palette(\"YlGnBu\", 10)\n",
    "sns.palplot(YlGnBu_palette)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.04864,
     "end_time": "2021-06-01T03:36:28.423690",
     "exception": false,
     "start_time": "2021-06-01T03:36:28.375050",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#### ✔️ This notebook will use this palettes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.067189,
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     "start_time": "2021-06-01T03:36:28.493353",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 3. Exploratory Data Analysis(EDA) with Visualization [Before Preprocessing]\n",
    "* Plot the target data percent\n",
    "* Plot the Keyword per Count\n",
    "* Number of alphabets by sentence / Number of words by sentence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "start_time": "2021-06-01T03:36:28.626184",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 3-1) Plot the target data percent"
   ]
  },
  {
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    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,2,figsize=(12,6))\n",
    "df['target'].value_counts().plot.pie(explode=[0, 0.1], autopct='%1.1f%%', ax=ax[0], shadow=True, colors=[YlGnBu_palette[2],YlGnBu_palette[3]])\n",
    "ax[0].set_title('Pie plot - target')\n",
    "sns.countplot('target', data=df, ax=ax[1], palette=[YlGnBu_palette[5],YlGnBu_palette[6]])\n",
    "ax[1].patch.set_alpha(0)\n",
    "ax[1].set_title('Count plot - target')\n",
    "\n",
    "fig.text(0.13,0.95,\"Plot the target data percent\", fontweight=\"bold\", fontfamily='serif', fontsize=20)\n",
    "plt.show()\n",
    "#target == 0 : negative(fake)\n",
    "#tarege == 1 : postive(real)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.042545,
     "end_time": "2021-06-01T03:36:29.356484",
     "exception": false,
     "start_time": "2021-06-01T03:36:29.313939",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 3-2) Plot the Keyword per Count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:29.446470Z",
     "iopub.status.busy": "2021-06-01T03:36:29.445889Z",
     "iopub.status.idle": "2021-06-01T03:36:29.448944Z",
     "shell.execute_reply": "2021-06-01T03:36:29.449358Z",
     "shell.execute_reply.started": "2021-06-01T03:27:18.910192Z"
    },
    "papermill": {
     "duration": 0.050942,
     "end_time": "2021-06-01T03:36:29.449505",
     "exception": false,
     "start_time": "2021-06-01T03:36:29.398563",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[nan 'ablaze' 'accident' 'aftershock' 'airplane%20accident' 'ambulance'\n",
      " 'annihilated' 'annihilation' 'apocalypse' 'armageddon' 'army' 'arson'\n",
      " 'arsonist' 'attack' 'attacked' 'avalanche' 'battle' 'bioterror'\n",
      " 'bioterrorism' 'blaze']\n"
     ]
    }
   ],
   "source": [
    "keyword_unique = df['keyword'].unique()\n",
    "print(keyword_unique[:20])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:29.555008Z",
     "iopub.status.busy": "2021-06-01T03:36:29.552552Z",
     "iopub.status.idle": "2021-06-01T03:36:30.383301Z",
     "shell.execute_reply": "2021-06-01T03:36:30.382871Z",
     "shell.execute_reply.started": "2021-06-01T03:27:18.921811Z"
    },
    "papermill": {
     "duration": 0.891667,
     "end_time": "2021-06-01T03:36:30.383449",
     "exception": false,
     "start_time": "2021-06-01T03:36:29.491782",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots(1,1,figsize=(16,6))\n",
    "sns.countplot('keyword',data=df,ax=ax,order=df['keyword'].value_counts().index, palette=sns.color_palette(\"YlGnBu\", 15))\n",
    "ax.set_xlim(0,15)\n",
    "ax.patch.set_alpha(0)\n",
    "fig.text(0.13,0.92,\"Count distribution by keyword in Tweets\", fontweight=\"bold\", fontfamily='serif', fontsize=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.043148,
     "end_time": "2021-06-01T03:36:30.470517",
     "exception": false,
     "start_time": "2021-06-01T03:36:30.427369",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 3-3) Number of alphabets by sentence / Number of words by sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:30.561374Z",
     "iopub.status.busy": "2021-06-01T03:36:30.560690Z",
     "iopub.status.idle": "2021-06-01T03:36:30.563410Z",
     "shell.execute_reply": "2021-06-01T03:36:30.563004Z",
     "shell.execute_reply.started": "2021-06-01T03:27:20.200593Z"
    },
    "papermill": {
     "duration": 0.049569,
     "end_time": "2021-06-01T03:36:30.563526",
     "exception": false,
     "start_time": "2021-06-01T03:36:30.513957",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_length(text):\n",
    "    return len(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:30.658582Z",
     "iopub.status.busy": "2021-06-01T03:36:30.657972Z",
     "iopub.status.idle": "2021-06-01T03:36:30.660784Z",
     "shell.execute_reply": "2021-06-01T03:36:30.660371Z",
     "shell.execute_reply.started": "2021-06-01T03:27:20.210023Z"
    },
    "papermill": {
     "duration": 0.05423,
     "end_time": "2021-06-01T03:36:30.660891",
     "exception": false,
     "start_time": "2021-06-01T03:36:30.606661",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df['length'] = df['text'].apply(get_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:30.751870Z",
     "iopub.status.busy": "2021-06-01T03:36:30.751070Z",
     "iopub.status.idle": "2021-06-01T03:36:30.754378Z",
     "shell.execute_reply": "2021-06-01T03:36:30.754818Z",
     "shell.execute_reply.started": "2021-06-01T03:27:20.231613Z"
    },
    "papermill": {
     "duration": 0.051034,
     "end_time": "2021-06-01T03:36:30.754934",
     "exception": false,
     "start_time": "2021-06-01T03:36:30.703900",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:30.861267Z",
     "iopub.status.busy": "2021-06-01T03:36:30.860411Z",
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   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize=(18,5))\n",
    "plt.hist(df[df['target'] == 0]['length'], alpha = 0.4, bins=150, label = 'Not', color=YlGnBu_palette[3])\n",
    "plt.hist(df[df['target'] == 1]['length'], alpha = 0.4, bins=150, label = 'Real', color=YlGnBu_palette[6])\n",
    "plt.xlabel('length')\n",
    "plt.ylabel('numbers')\n",
    "plt.legend(loc='upper right')\n",
    "plt.xlim(0,150)\n",
    "ax.set_ylabel('')\n",
    "ax.patch.set_alpha(0)\n",
    "fig.text(0.13,0.8,\"Count distribution by length in Tweets\", fontweight=\"bold\", fontfamily='serif', fontsize=25)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.045931,
     "end_time": "2021-06-01T03:36:31.515804",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.469873",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 4. Prepocessing Data\n",
    "* Null value processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:31.611297Z",
     "iopub.status.busy": "2021-06-01T03:36:31.610530Z",
     "iopub.status.idle": "2021-06-01T03:36:31.616371Z",
     "shell.execute_reply": "2021-06-01T03:36:31.615972Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.120047Z"
    },
    "papermill": {
     "duration": 0.056345,
     "end_time": "2021-06-01T03:36:31.616496",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.560151",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id             0\n",
       "keyword       61\n",
       "location    2533\n",
       "text           0\n",
       "target         0\n",
       "length         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:31.715227Z",
     "iopub.status.busy": "2021-06-01T03:36:31.714489Z",
     "iopub.status.idle": "2021-06-01T03:36:31.720185Z",
     "shell.execute_reply": "2021-06-01T03:36:31.719696Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.137748Z"
    },
    "papermill": {
     "duration": 0.058944,
     "end_time": "2021-06-01T03:36:31.720283",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.661339",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id          0\n",
       "keyword     0\n",
       "location    0\n",
       "text        0\n",
       "target      0\n",
       "length      0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['keyword'].fillna(\"\", inplace = True)\n",
    "df['location'].fillna(\"\",inplace = True)\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.044314,
     "end_time": "2021-06-01T03:36:31.809325",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.765011",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 5. Feature Enginnering \n",
    "* Text data to nomalization\n",
    "* Use SpellChecker libray\n",
    "* Plot WordClouds\n",
    "* Drop unuseful columns\n",
    "* Text data tokenization\n",
    "* Text data to fit on Glove Embedding"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.044534,
     "end_time": "2021-06-01T03:36:31.899061",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.854527",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-1) Text data to nomalization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:31.994556Z",
     "iopub.status.busy": "2021-06-01T03:36:31.993950Z",
     "iopub.status.idle": "2021-06-01T03:36:31.998446Z",
     "shell.execute_reply": "2021-06-01T03:36:31.998009Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.159351Z"
    },
    "papermill": {
     "duration": 0.054289,
     "end_time": "2021-06-01T03:36:31.998566",
     "exception": false,
     "start_time": "2021-06-01T03:36:31.944277",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "stop_words = stopwords.words('english')\n",
    "stemmer = SnowballStemmer('english')\n",
    "lemmatizer = WordNetLemmatizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:32.098008Z",
     "iopub.status.busy": "2021-06-01T03:36:32.097180Z",
     "iopub.status.idle": "2021-06-01T03:36:32.099939Z",
     "shell.execute_reply": "2021-06-01T03:36:32.099546Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.171124Z"
    },
    "papermill": {
     "duration": 0.056185,
     "end_time": "2021-06-01T03:36:32.100051",
     "exception": false,
     "start_time": "2021-06-01T03:36:32.043866",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def preprocess(text,stem=False):\n",
    "    text = text.lower()  # lowercase\n",
    "\n",
    "    text = re.sub(r'[!]+', '!', text)\n",
    "    text = re.sub(r'[?]+', '?', text)\n",
    "    text = re.sub(r'[.]+', '.', text)\n",
    "    text = re.sub(r\"'\", \"\", text)\n",
    "    text = re.sub('\\s+', ' ', text).strip()  # Remove and double spaces\n",
    "    text = re.sub(r'&amp;?', r'and', text)  # replace & -> and\n",
    "    text = re.sub(r\"https?:\\/\\/t.co\\/[A-Za-z0-9]+\", \"\", text)  # Remove URLs\n",
    "    # remove some puncts (except . ! # ?)\n",
    "    text = re.sub(r'[:\"$%&\\*+,-/:;<=>@\\\\^_`{|}~]+', '', text)\n",
    "    emoji_pattern = re.compile(\"[\"\n",
    "                               u\"\\U0001F600-\\U0001F64F\"  # emoticons\n",
    "                               u\"\\U0001F300-\\U0001F5FF\"  # symbols & pictographs\n",
    "                               u\"\\U0001F680-\\U0001F6FF\"  # transport & map symbols\n",
    "                               u\"\\U0001F1E0-\\U0001F1FF\"  # flags (iOS)\n",
    "                               u\"\\U00002702-\\U000027B0\"\n",
    "                               u\"\\U000024C2-\\U0001F251\"\n",
    "                               \"]+\", flags=re.UNICODE)\n",
    "    text = emoji_pattern.sub(r'EMOJI', text)\n",
    "    \n",
    "    tokens = []\n",
    "    for token in text.split():\n",
    "        if token not in stop_words:\n",
    "            if stem:\n",
    "                tokens.append(SnowballStemmer.stem(token))\n",
    "            else:\n",
    "                tokens.append(token)\n",
    "    return \" \".join(tokens)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.044881,
     "end_time": "2021-06-01T03:36:32.189896",
     "exception": false,
     "start_time": "2021-06-01T03:36:32.145015",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-2) Use SpellChecker libray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:32.285562Z",
     "iopub.status.busy": "2021-06-01T03:36:32.284780Z",
     "iopub.status.idle": "2021-06-01T03:36:32.405033Z",
     "shell.execute_reply": "2021-06-01T03:36:32.404568Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.185806Z"
    },
    "papermill": {
     "duration": 0.169951,
     "end_time": "2021-06-01T03:36:32.405166",
     "exception": false,
     "start_time": "2021-06-01T03:36:32.235215",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "spell = SpellChecker()\n",
    "def correct_spell(text):\n",
    "    corrected_text = []\n",
    "    misspelled_words = spell.unknown(text.split())\n",
    "    for word in text.split():\n",
    "        if word in misspelled_words:\n",
    "            corrected_text.append(spell.correction(word))\n",
    "        else:\n",
    "            corrected_text.append(word)\n",
    "    return \" \".join(corrected_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:32.500748Z",
     "iopub.status.busy": "2021-06-01T03:36:32.500070Z",
     "iopub.status.idle": "2021-06-01T03:36:32.504364Z",
     "shell.execute_reply": "2021-06-01T03:36:32.504883Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.348557Z"
    },
    "papermill": {
     "duration": 0.054593,
     "end_time": "2021-06-01T03:36:32.505013",
     "exception": false,
     "start_time": "2021-06-01T03:36:32.450420",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'correct'"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "text = \"corect\"\n",
    "correct_spell(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:32.605114Z",
     "iopub.status.busy": "2021-06-01T03:36:32.604359Z",
     "iopub.status.idle": "2021-06-01T03:36:32.997182Z",
     "shell.execute_reply": "2021-06-01T03:36:32.996724Z",
     "shell.execute_reply.started": "2021-06-01T03:27:21.362003Z"
    },
    "papermill": {
     "duration": 0.447314,
     "end_time": "2021-06-01T03:36:32.997298",
     "exception": false,
     "start_time": "2021-06-01T03:36:32.549984",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "df.text = df.text.apply(lambda x: preprocess(x))\n",
    "#df.text = df.text.apply(lambda x: correct_spell(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.048495,
     "end_time": "2021-06-01T03:36:33.093062",
     "exception": false,
     "start_time": "2021-06-01T03:36:33.044567",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-3) Plot Word Cloud\n",
    "* fake target\n",
    "* real target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:33.187705Z",
     "iopub.status.busy": "2021-06-01T03:36:33.187163Z",
     "iopub.status.idle": "2021-06-01T03:36:33.203005Z",
     "shell.execute_reply": "2021-06-01T03:36:33.202476Z",
     "shell.execute_reply.started": "2021-06-01T03:29:16.816901Z"
    },
    "papermill": {
     "duration": 0.064758,
     "end_time": "2021-06-01T03:36:33.203132",
     "exception": false,
     "start_time": "2021-06-01T03:36:33.138374",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "mask_dir = np.array(Image.open('../input/masksforwordclouds/twitter_mask3.jpg'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:33.316363Z",
     "iopub.status.busy": "2021-06-01T03:36:33.315572Z",
     "iopub.status.idle": "2021-06-01T03:36:35.874407Z",
     "shell.execute_reply": "2021-06-01T03:36:35.873984Z",
     "shell.execute_reply.started": "2021-06-01T03:35:47.682929Z"
    },
    "papermill": {
     "duration": 2.626007,
     "end_time": "2021-06-01T03:36:35.874532",
     "exception": false,
     "start_time": "2021-06-01T03:36:33.248525",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,2, figsize=(18,9))\n",
    "target_list = np.unique(df['target'])\n",
    "\n",
    "for i, target in zip(range(2), target_list):\n",
    "    wc = WordCloud(background_color=\"white\", max_words = 2000, width = 1600, height = 800, mask=mask_dir, colormap=\"Blues\").generate(\" \".join(df[df['target']==target]['text']))\n",
    "    \n",
    "    if target == 0:\n",
    "        axes[i].text(0.5,1, \"Fake text\", fontweight=\"bold\", fontfamily='serif', fontsize=17)\n",
    "    else:\n",
    "        axes[i].text(0.5,1, \"Reak text\", fontweight=\"bold\", fontfamily='serif', fontsize=17)\n",
    "    axes[i].patch.set_alpha(0)\n",
    "    axes[i].axis('off')\n",
    "    axes[i].imshow(wc)\n",
    "\n",
    "fig.text(0.1, 0.9,\"WordCloud by target per text in Tweets\", fontweight=\"bold\", fontfamily='serif', fontsize=22)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.05295,
     "end_time": "2021-06-01T03:36:35.981087",
     "exception": false,
     "start_time": "2021-06-01T03:36:35.928137",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-4) Drop unuseful columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:36.098182Z",
     "iopub.status.busy": "2021-06-01T03:36:36.097318Z",
     "iopub.status.idle": "2021-06-01T03:36:36.101365Z",
     "shell.execute_reply": "2021-06-01T03:36:36.100962Z"
    },
    "papermill": {
     "duration": 0.067983,
     "end_time": "2021-06-01T03:36:36.101493",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.033510",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>keyword</th>\n",
       "      <th>location</th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>deeds reason #earthquake may allah forgive us</td>\n",
       "      <td>1</td>\n",
       "      <td>69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>forest fire near la ronge sask canada</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>residents asked shelter place notified officer...</td>\n",
       "      <td>1</td>\n",
       "      <td>133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>13000 people receive #wildfires evacuation ord...</td>\n",
       "      <td>1</td>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>got sent photo ruby #alaska smoke #wildfires p...</td>\n",
       "      <td>1</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>#rockyfire update california hwy 20 closed dir...</td>\n",
       "      <td>1</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>#flood #disaster heavy rain causes flash flood...</td>\n",
       "      <td>1</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>im top hill see fire woods</td>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>theres emergency evacuation happening building...</td>\n",
       "      <td>1</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>15</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>im afraid tornado coming area</td>\n",
       "      <td>1</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id keyword location                                               text  \\\n",
       "0   1                       deeds reason #earthquake may allah forgive us   \n",
       "1   4                               forest fire near la ronge sask canada   \n",
       "2   5                   residents asked shelter place notified officer...   \n",
       "3   6                   13000 people receive #wildfires evacuation ord...   \n",
       "4   7                   got sent photo ruby #alaska smoke #wildfires p...   \n",
       "5   8                   #rockyfire update california hwy 20 closed dir...   \n",
       "6  10                   #flood #disaster heavy rain causes flash flood...   \n",
       "7  13                                          im top hill see fire woods   \n",
       "8  14                   theres emergency evacuation happening building...   \n",
       "9  15                                       im afraid tornado coming area   \n",
       "\n",
       "   target  length  \n",
       "0       1      69  \n",
       "1       1      38  \n",
       "2       1     133  \n",
       "3       1      65  \n",
       "4       1      88  \n",
       "5       1     110  \n",
       "6       1      95  \n",
       "7       1      59  \n",
       "8       1      79  \n",
       "9       1      52  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:36.218212Z",
     "iopub.status.busy": "2021-06-01T03:36:36.217355Z",
     "iopub.status.idle": "2021-06-01T03:36:36.221164Z",
     "shell.execute_reply": "2021-06-01T03:36:36.220759Z"
    },
    "papermill": {
     "duration": 0.066528,
     "end_time": "2021-06-01T03:36:36.221273",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.154745",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>deeds reason #earthquake may allah forgive us</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>forest fire near la ronge sask canada</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>residents asked shelter place notified officer...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>13000 people receive #wildfires evacuation ord...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>got sent photo ruby #alaska smoke #wildfires p...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>#rockyfire update california hwy 20 closed dir...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>#flood #disaster heavy rain causes flash flood...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>im top hill see fire woods</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>theres emergency evacuation happening building...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>im afraid tornado coming area</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text  target\n",
       "0      deeds reason #earthquake may allah forgive us       1\n",
       "1              forest fire near la ronge sask canada       1\n",
       "2  residents asked shelter place notified officer...       1\n",
       "3  13000 people receive #wildfires evacuation ord...       1\n",
       "4  got sent photo ruby #alaska smoke #wildfires p...       1\n",
       "5  #rockyfire update california hwy 20 closed dir...       1\n",
       "6  #flood #disaster heavy rain causes flash flood...       1\n",
       "7                         im top hill see fire woods       1\n",
       "8  theres emergency evacuation happening building...       1\n",
       "9                      im afraid tornado coming area       1"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(['keyword','id','location','length'],axis=1,inplace=True)\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.053265,
     "end_time": "2021-06-01T03:36:36.328687",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.275422",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-5) Text data tokenization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:36.440992Z",
     "iopub.status.busy": "2021-06-01T03:36:36.440228Z",
     "iopub.status.idle": "2021-06-01T03:36:36.446405Z",
     "shell.execute_reply": "2021-06-01T03:36:36.447069Z"
    },
    "papermill": {
     "duration": 0.064811,
     "end_time": "2021-06-01T03:36:36.447234",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.382423",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Data size :  6090\n",
      "Test Data size :  1523\n"
     ]
    }
   ],
   "source": [
    "train_data, test_data = train_test_split(df,test_size = 0.2)\n",
    "print(\"Train Data size : \",len(train_data))\n",
    "print(\"Test Data size : \",len(test_data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:36.565195Z",
     "iopub.status.busy": "2021-06-01T03:36:36.564283Z",
     "iopub.status.idle": "2021-06-01T03:36:36.568247Z",
     "shell.execute_reply": "2021-06-01T03:36:36.567861Z"
    },
    "papermill": {
     "duration": 0.064915,
     "end_time": "2021-06-01T03:36:36.568362",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.503447",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6269</th>\n",
       "      <td>bad say im kinda afraid storms storm? help</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1151</th>\n",
       "      <td>japan marks 70th anniversary hiroshima atomic ...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5239</th>\n",
       "      <td>justifying quarrel would one day end obliterat...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5587</th>\n",
       "      <td>latest homes razed northern california wildfir...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3289</th>\n",
       "      <td>make sure evacuate past fire doors questions? ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4835</th>\n",
       "      <td>media needs stop publicizing mass murder many ...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1269</th>\n",
       "      <td>wildlionx3 others dont get burned</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4744</th>\n",
       "      <td>tried making chocolate peanut butter lava cake...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>dog rendered kitten burning buildings</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3352</th>\n",
       "      <td>ahrar al sham negotiations iran al zabadani wa...</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   text  target\n",
       "6269         bad say im kinda afraid storms storm? help       1\n",
       "1151  japan marks 70th anniversary hiroshima atomic ...       1\n",
       "5239  justifying quarrel would one day end obliterat...       0\n",
       "5587  latest homes razed northern california wildfir...       1\n",
       "3289  make sure evacuate past fire doors questions? ...       0\n",
       "4835  media needs stop publicizing mass murder many ...       0\n",
       "1269                  wildlionx3 others dont get burned       0\n",
       "4744  tried making chocolate peanut butter lava cake...       0\n",
       "1359              dog rendered kitten burning buildings       1\n",
       "3352  ahrar al sham negotiations iran al zabadani wa...       0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:36.692310Z",
     "iopub.status.busy": "2021-06-01T03:36:36.691275Z",
     "iopub.status.idle": "2021-06-01T03:36:36.786684Z",
     "shell.execute_reply": "2021-06-01T03:36:36.786250Z"
    },
    "papermill": {
     "duration": 0.163971,
     "end_time": "2021-06-01T03:36:36.786797",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.622826",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vocab size :  15556\n"
     ]
    }
   ],
   "source": [
    "tokenizer = Tokenizer()\n",
    "tokenizer.fit_on_texts(train_data.text)\n",
    "word_index = tokenizer.word_index\n",
    "vocab_size = len(word_index) + 1\n",
    "print(\"Vocab size : \",vocab_size)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.054794,
     "end_time": "2021-06-01T03:36:36.896809",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.842015",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 5-6) Text data to fit on Glove Embedding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:37.030472Z",
     "iopub.status.busy": "2021-06-01T03:36:37.025334Z",
     "iopub.status.idle": "2021-06-01T03:36:37.156626Z",
     "shell.execute_reply": "2021-06-01T03:36:37.157192Z"
    },
    "papermill": {
     "duration": 0.205191,
     "end_time": "2021-06-01T03:36:37.157371",
     "exception": false,
     "start_time": "2021-06-01T03:36:36.952180",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training X Shape: (6090, 30)\n",
      "Testing X Shape: (1523, 30)\n"
     ]
    }
   ],
   "source": [
    "x_train = pad_sequences(tokenizer.texts_to_sequences(train_data.text), maxlen = 30)\n",
    "x_test = pad_sequences(tokenizer.texts_to_sequences(test_data.text), maxlen = 30)\n",
    "\n",
    "\n",
    "print(\"Training X Shape:\",x_train.shape)\n",
    "print(\"Testing X Shape:\",x_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:37.276906Z",
     "iopub.status.busy": "2021-06-01T03:36:37.276095Z",
     "iopub.status.idle": "2021-06-01T03:36:37.280671Z",
     "shell.execute_reply": "2021-06-01T03:36:37.280096Z"
    },
    "papermill": {
     "duration": 0.066811,
     "end_time": "2021-06-01T03:36:37.280798",
     "exception": false,
     "start_time": "2021-06-01T03:36:37.213987",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y_train shape: (6090,)\n",
      "y_test shape: (1523,)\n",
      "6269    1\n",
      "1151    1\n",
      "5239    0\n",
      "5587    1\n",
      "3289    0\n",
      "       ..\n",
      "4249    0\n",
      "6055    1\n",
      "1356    1\n",
      "6246    1\n",
      "6751    0\n",
      "Name: target, Length: 6090, dtype: int64 5568    1\n",
      "6020    0\n",
      "5615    0\n",
      "5875    0\n",
      "5872    0\n",
      "       ..\n",
      "5581    1\n",
      "6855    1\n",
      "4493    0\n",
      "1607    0\n",
      "5       1\n",
      "Name: target, Length: 1523, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "y_train = train_data.target\n",
    "y_test = test_data.target\n",
    "\n",
    "print(\"y_train shape:\", y_train.shape)\n",
    "print(\"y_test shape:\", y_test.shape)\n",
    "print(y_train,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:37.397811Z",
     "iopub.status.busy": "2021-06-01T03:36:37.397068Z",
     "iopub.status.idle": "2021-06-01T03:36:37.399706Z",
     "shell.execute_reply": "2021-06-01T03:36:37.399290Z"
    },
    "papermill": {
     "duration": 0.062627,
     "end_time": "2021-06-01T03:36:37.399813",
     "exception": false,
     "start_time": "2021-06-01T03:36:37.337186",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "GLOVE_EMB = '/kaggle/input/glove6b/glove.6B.300d.txt'\n",
    "EMBEDDING_DIM = 300\n",
    "LR = 1e-3\n",
    "BATCH_SIZE = 512"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:36:37.515583Z",
     "iopub.status.busy": "2021-06-01T03:36:37.515063Z",
     "iopub.status.idle": "2021-06-01T03:37:19.076320Z",
     "shell.execute_reply": "2021-06-01T03:37:19.076739Z"
    },
    "papermill": {
     "duration": 41.621289,
     "end_time": "2021-06-01T03:37:19.076896",
     "exception": false,
     "start_time": "2021-06-01T03:36:37.455607",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 400000 word vectors.\n"
     ]
    }
   ],
   "source": [
    "embeddings_index = {}\n",
    "\n",
    "f = open(GLOVE_EMB)\n",
    "for line in f:\n",
    "    values = line.split()\n",
    "    word = value = values[0]\n",
    "    coefs = np.asarray(values[1:], dtype='float32')\n",
    "    embeddings_index[word] = coefs\n",
    "f.close()\n",
    "\n",
    "print('Found %s word vectors.' %len(embeddings_index))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:19.196362Z",
     "iopub.status.busy": "2021-06-01T03:37:19.195633Z",
     "iopub.status.idle": "2021-06-01T03:37:19.240733Z",
     "shell.execute_reply": "2021-06-01T03:37:19.240189Z"
    },
    "papermill": {
     "duration": 0.106906,
     "end_time": "2021-06-01T03:37:19.240860",
     "exception": false,
     "start_time": "2021-06-01T03:37:19.133954",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "embedding_matrix = np.zeros((vocab_size, EMBEDDING_DIM))\n",
    "for word, i in word_index.items():\n",
    "    embedding_vector = embeddings_index.get(word)\n",
    "    if embedding_vector is not None:\n",
    "        embedding_matrix[i] = embedding_vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:19.359352Z",
     "iopub.status.busy": "2021-06-01T03:37:19.358860Z",
     "iopub.status.idle": "2021-06-01T03:37:19.373214Z",
     "shell.execute_reply": "2021-06-01T03:37:19.372820Z"
    },
    "papermill": {
     "duration": 0.074332,
     "end_time": "2021-06-01T03:37:19.373322",
     "exception": false,
     "start_time": "2021-06-01T03:37:19.298990",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "embedding_layer = tf.keras.layers.Embedding(vocab_size,\n",
    "                                            EMBEDDING_DIM,\n",
    "                                            weights=[embedding_matrix],                                            \n",
    "                                            input_length=30,\n",
    "                                           trainable=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.056783,
     "end_time": "2021-06-01T03:37:19.487086",
     "exception": false,
     "start_time": "2021-06-01T03:37:19.430303",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 6. Modeling\n",
    "* Glove & LSTM Modeling\n",
    "* Training\n",
    "* Plot model's loss / accuray values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.057383,
     "end_time": "2021-06-01T03:37:19.601157",
     "exception": false,
     "start_time": "2021-06-01T03:37:19.543774",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 6-1) Glove & LSTM Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:19.722233Z",
     "iopub.status.busy": "2021-06-01T03:37:19.719140Z",
     "iopub.status.idle": "2021-06-01T03:37:22.608497Z",
     "shell.execute_reply": "2021-06-01T03:37:22.608004Z"
    },
    "papermill": {
     "duration": 2.950954,
     "end_time": "2021-06-01T03:37:22.608638",
     "exception": false,
     "start_time": "2021-06-01T03:37:19.657684",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "inputs = Input(shape=(30,),dtype = 'int32')\n",
    "\n",
    "embedding = embedding_layer(inputs)\n",
    "net = SpatialDropout1D(0.2)(embedding)\n",
    "net = Bidirectional(LSTM(64,dropout=0.2, recurrent_dropout=0.2))(net)\n",
    "net = Dense(1,activation = 'sigmoid')(net)\n",
    "\n",
    "outputs = net\n",
    "model = tf.keras.Model(inputs,outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:22.733230Z",
     "iopub.status.busy": "2021-06-01T03:37:22.732725Z",
     "iopub.status.idle": "2021-06-01T03:37:22.739872Z",
     "shell.execute_reply": "2021-06-01T03:37:22.739269Z"
    },
    "papermill": {
     "duration": 0.073421,
     "end_time": "2021-06-01T03:37:22.739991",
     "exception": false,
     "start_time": "2021-06-01T03:37:22.666570",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer = Adam(learning_rate = LR),\n",
    "             loss = 'binary_crossentropy',\n",
    "             metrics = ['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:22.858629Z",
     "iopub.status.busy": "2021-06-01T03:37:22.857406Z",
     "iopub.status.idle": "2021-06-01T03:37:22.859864Z",
     "shell.execute_reply": "2021-06-01T03:37:22.860308Z"
    },
    "papermill": {
     "duration": 0.063484,
     "end_time": "2021-06-01T03:37:22.860450",
     "exception": false,
     "start_time": "2021-06-01T03:37:22.796966",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "callback = ReduceLROnPlateau(factor=0.1,\n",
    "                    min_lr = 0.01,\n",
    "                    monitor = 'val_loss',\n",
    "                    verbose = 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.056614,
     "end_time": "2021-06-01T03:37:22.973641",
     "exception": false,
     "start_time": "2021-06-01T03:37:22.917027",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 6-2) Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:23.092897Z",
     "iopub.status.busy": "2021-06-01T03:37:23.092371Z",
     "iopub.status.idle": "2021-06-01T03:37:57.080988Z",
     "shell.execute_reply": "2021-06-01T03:37:57.080131Z"
    },
    "papermill": {
     "duration": 34.050493,
     "end_time": "2021-06-01T03:37:57.081119",
     "exception": false,
     "start_time": "2021-06-01T03:37:23.030626",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "12/12 [==============================] - 8s 317ms/step - loss: 0.6574 - accuracy: 0.6303 - val_loss: 0.5326 - val_accuracy: 0.7649\n",
      "Epoch 2/10\n",
      "12/12 [==============================] - 3s 228ms/step - loss: 0.5178 - accuracy: 0.7665 - val_loss: 0.4517 - val_accuracy: 0.7951\n",
      "Epoch 3/10\n",
      "12/12 [==============================] - 3s 248ms/step - loss: 0.4603 - accuracy: 0.7943 - val_loss: 0.4274 - val_accuracy: 0.8221\n",
      "Epoch 4/10\n",
      "12/12 [==============================] - 3s 223ms/step - loss: 0.4428 - accuracy: 0.8052 - val_loss: 0.4231 - val_accuracy: 0.8207\n",
      "Epoch 5/10\n",
      "12/12 [==============================] - 3s 226ms/step - loss: 0.4256 - accuracy: 0.8105 - val_loss: 0.4167 - val_accuracy: 0.8201\n",
      "Epoch 6/10\n",
      "12/12 [==============================] - 3s 237ms/step - loss: 0.4242 - accuracy: 0.8145 - val_loss: 0.4215 - val_accuracy: 0.8201\n",
      "Epoch 7/10\n",
      "12/12 [==============================] - 3s 237ms/step - loss: 0.4077 - accuracy: 0.8151 - val_loss: 0.4147 - val_accuracy: 0.8240\n",
      "Epoch 8/10\n",
      "12/12 [==============================] - 3s 232ms/step - loss: 0.4061 - accuracy: 0.8226 - val_loss: 0.4149 - val_accuracy: 0.8247\n",
      "Epoch 9/10\n",
      "12/12 [==============================] - 3s 236ms/step - loss: 0.3914 - accuracy: 0.8303 - val_loss: 0.4130 - val_accuracy: 0.8240\n",
      "Epoch 10/10\n",
      "12/12 [==============================] - 3s 247ms/step - loss: 0.3805 - accuracy: 0.8388 - val_loss: 0.4170 - val_accuracy: 0.8234\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(x_train,\n",
    "                    y_train,\n",
    "                    batch_size=512,\n",
    "                    epochs=10,\n",
    "                    validation_data=(x_test, y_test),\n",
    "                    callbacks = [callback])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.094909,
     "end_time": "2021-06-01T03:37:57.269418",
     "exception": false,
     "start_time": "2021-06-01T03:37:57.174509",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "### 6-3) Plot model's loss / accuray values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:57.482267Z",
     "iopub.status.busy": "2021-06-01T03:37:57.481158Z",
     "iopub.status.idle": "2021-06-01T03:37:57.836872Z",
     "shell.execute_reply": "2021-06-01T03:37:57.837268Z"
    },
    "papermill": {
     "duration": 0.470951,
     "end_time": "2021-06-01T03:37:57.837424",
     "exception": false,
     "start_time": "2021-06-01T03:37:57.366473",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
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qMxXfowX5xEJ9SsV3rHSn+AYwx4wfRTGywjiuPB6OG0dxrqMoPH5l+jJUnFGoTF9mtCD2p4+bVRy/wphRFJhuwVBYJ9r6dTw21qKhtVfHWvvU3Tc8bj+vx6XivJHVyBkqLchUSUGmcjL9/H8dAHBBElowG2N+LGmVJFvS71uW9U7cc9+U9OuSwpLetSzrW7Htfynphli2H1iW9VQiMwJAMrBtW5+2f6FtNc/rRF+TvG6vblmyXreWrVe6L93peOO4XC55XJ7YH75TnI4ziuJ7PI/LI7fLJbfLHf1S7LvLJZfLLY/LPe67W66xn11j+44dN2F77GeXoueY/LzR48fO65L7DLnGvYZccrs9cuvU87pdrujruqOvf07nHdlXce+BP7QD024oPHzKauLeYJ/64mYV9wX71BPb1hea+iiKQGwURWnmImXEjZ0YHUkxbhRFhvwe3wy8Y0CK2LbauwbHj7do7VXzyQFF7PE33cvLStWVVXlxN93L0MIF6fJ63A6lBwDMZwkrmI0x6yQttSxrtTHmEkm/kLQy9lyWpD+SVG1ZVsgYs9MYs0pSmqTLYsfkSXpfEgUzAFyA2q56ba3ZocOdtXLJpdXFy3VXxS3KTc1xOtqcMleK74ll9IUV3+PPFV98R+ywIratiCKK2BO/opkikaCGNLbNtiMK25Gx77LP/gbnAddo2TxWZrvljv2amqR0n1BQjyuyNcm+8eV7rBCf/LyTHT+hdJ9QpI/lHV/Ex7/22OtOft7hlD519PU5/a8Bc0DIDscK4/5Ty+PRx+c2iiLDm64Mf7oK0vOU6cscm1kcG0URiF9l7E9nFAVmjb7B4Nh4i9axQnloODxuv7QUjypLslQaK5EXF2aqJD9T6an8ZWUAwMxJ5P91bpa0VZIsy/rMGJNrjMmyLKtb0nDsK9MY0yspXdJJSTWS3o4d3yEpwxjjsSwrfMrZAQBn1NzXou1HXtAHrZ9Iki7Pv0SbKm/Xoswih5NhOs3W4nsqbNuWLXu0dB5XUGtiYR0eK67tSNzz9rhy27Zthe3w6Hkj8YX2KcfbpynHw4posvPGjotEv4++1pTPGznlfY1ki35IEIw774R/JrE8QDLze/wK+DJUnLFwbPyEP320OB7bxigKzB2hcERN7bHxFq29amjt07GWXnX0DI3bz+1yqTgvXSVxN9xbXJChvCw+FAEAOC+RBXORpANxj5tj27otyxo0xnxP0hFJ/ZJ+aVnWwdh+I0tcvippx9nK5dzcdHm9yfkbx4KCgNMRAMxCHQNdevzT5/TqkX2K2BEty6vUr125RRcXLJ3S8VxbgNnJtu3RMjscVz7H/xyJTL49HJlYeE/h+dOcK74gD0fCE563FYlti8QV8MBE4YitgaFQ9Gs4pMGhkIJBWxneaEEcSM1UTlqWFqQHlJeRrYLMLOVkpisjzacUH3PgMfd+v2LHxlvUNXarrrFb9bHvx1t6FAqPv04uyErVNaZQ5cVZKivOUsWiLC0uzJQvSf/cC8ykuXZtAWaLRBbME3/X51J0FvPIiIw/lbRMUrekV40xV1qW9WHs+c2SfkfSrWd7kY6O/unMPGcUFATU2trjdAwAs8hAaEAv1b+mV4/tUTAS1ML0Qm2uul1X5F8ql1xTumZwbQHmKpckjyRP3E9n2X2G+jmuK8nHtm31D4XU3jWo9q5BtXVHv7d3D6ottq134GwjLkKK/gXHk6c843G7lJ7qVXqKd/R7Wqpv3OPx331Ki3vs9zIbfa6b7deVgaGQGtpioy1Gxly09Kp/aPx9E/w+t0oLAyotzFBJQWZ0zEVhpjLTTp3r3Zmkf+4FZtJsv7YAs8HpPoRJZMHcoOiK5RGLJDXFfr5Y0hHLstokyRizR9K1kj40xtwm6c8k3W5ZVlcC8wHAvBCMhLTn+H69UP+q+oL9yvZn6a7KTVpVdB1/NRgAMO1s21Z33/C44nikTG7vjn4NDE3+lxC9HrfyslNVtjBTedmpystKHf0eSPdrcDis/qGg+gdD6h8KaSD2vX/c97HnO3qGNBw6t/ExFNSYLuFIRC0dAzoeG2vR0NqrYy29ausaHLefS1LhgnRdXJ6r0oLMaJlcmKH8nDS5+bUEAJgHElkw75T0PUk/NcZcLemEZVkjHwXVSbrYGJMmaVDSdZJ2GGOyJf1I0pcsyzp1uQIAYFTEjuidpvf1bO1OnRzsUJo3VZsr79D60jXye/xOxwMAzFHhSESdPcNq6xoYK4+7R1YjD+lk96CCpyl1U/0e5WWnKn+kOI4rkfOzUhXI8E97oRYMRTQwNHkB7URBnZYyWUntVXpsH7+Pgnou6uobjq1GHluV3NDWp1B4/K+fzDSfLi7Ljc5Jjt10b1F+hlJ8fOgPAJi/ElYwW5a13xhzwBizX1JE0jeNMQ9L6rIs62ljzI8k7VL077/ttyxrjzHm65LyJT1mjBk51W9alnU0UTkBYK6xbVufnTyobTU71NDbKK/Lo5tLb9St5RuU6ctwOh4AYJYLhiI62T02uqKta3yJ3NEzpMhpZmdnpvm0KD9jXIEc/3N6infGy1Of1y2f16+sjPP7cNWJgjptiqulKahn3lAwrBOj4y1i31t71dM/fqyL1+NWSX6GFhfExlvEbrqXleHn3w8AIOm45vqNV1pbe+b2GzhPzAYCklN99zFtPbxDBztr5JJLK4qu0V0VtyovLXdazs+1BcB047oy8waGQqeuPI77uatveNLjXJJyAinjxlbkZacqf+TnrFSl+FmFOdGFFNQDgyEK6vMwHdeViG2rrXNgdD7y8dZeHWvtU0tHvyb+ETk/OzW6IjlWIpcWZqowN00et/uCMgCYXfg9C3B2BQWBSX8TkcgRGQCAadLS36rtR17U+y0fSZIuy7tIm6ruUElmscPJAAAzybZt9Q4Ex809bpswA7lvMDTpsR63SwuyUnTRkpxTRlfk5aRpQSBFXg+F2blycgV1Jyuop6R3IDg23qI1Nt6itU9DwfGzwtNTvFpakh0rkqOFckl+htJS+GMzAABnwv8pAWAW6xrq0fN1L2vfibcUsSMqz1qiLVV3aGluldPRAAAJELFtdfUOx4rjgVhpPDRuNfLEUmyE3xu9gV7FoqyxsRVx33MyU+R2z61iMBlQUE+fYCiixvZoeXysdWxecmfv+FX7HrdLxXnp41YlLy7IVG4gZc6V5wAAzAYUzAAwCw2EBvXK0df0ytHXNRwJqjA9X5sr79CVBZfxBx8AmMNC4Yg6eoZOGVsx8v1kz6BC4cknwKWneFWYm3bq6IrY/ONAmo//RyShZCyobdtWe9egjrX2qqG1V8daetXQ2qemk/0KR8b/95MbSNHllXlaXBgtkUsLMlWUl85qfQAAphEFMwDMIsFISHsb3tQLda+oN9inbH9A91XcrdXFy+VxM/cSAGa7oWBYJ7tPHV0x8nNn79Ap811HZGX4VVoYOOXGeSM/89f0kQhzsaD2et0aGh6/kj/F71F5cSC6Krkgtiq5MFMZqb7zel8AAGDq+F0qAMwCETuiA80f6pkjL6p98KRSPam6u/J2bShdqxTP+f2BDwAw/foHg6esPG6Lm3/c0x+c9DiXS1oQSNHSkuzR4nhsJXJ0/rHfxweJmHucKKhtOzpPvDQ22mJxYabyslPlZgU/AACOoGAGAAfZtq0vTh7S1podOt57Ql6XRzeV3qDbym5Spj/D6XgAkFRs21Z3f3DcyIpxJXL3gAaGJp9/7PW4tCArVYsLMqOjK2IF8sgYixxuoAdM6nwK6oKCgFpbexKYCgAAnAsKZgBwSH33MW2reV5Wx2G55NKKomu0seJW5aUtcDoaAMxLkYitzt6h0RXHbRPnH3cPnvav66f4PdFRFYvjiuO4VchZGX5WTwIAACApUTADwAxr6W/Ts0de1IGWDyVJl+QZba68Q4sDixxOBgBzWzAU0cmewbEb6E0YZdHRM3TKDcBGZKb5VJyXMWF0xdjPGalebqAHAAAATIKCGQBmSPdwj56vfUV7T7ypiB1RWaBUW6rv0LLcaqejAcCcMDgcGlcaT7yJXnfvsE5z/zxlZ/pVXhwYK4+zxq9ATvXz22IAAADgfPA7aQBIsMHQoF45+rpePva6hsPDKkjL06aqO3R1weWshgOAGNu21TcYGlt9PO4megNq7xpU32Bo0mM9bpdyAylaVppzyuiKvOxULQikyudl/jEAAACQCBTMAJAgoUhIe0+8pedrX1ZvsE8Bf6buqbpLaxatkMftcToeAMyoiG2rq3d4XHE8cTXy0PDkN9Dzed3Ky0pVeXHWKeMr8rNTlZOZIrebD+wAAAAAJ1AwA8A0i9gRvdfykZ6peUFtgyeV4vFrY8Wt2lB6g1K9KU7HA4CE6RsMqrVzQC0dA2rtjH519QfV2Nank92DCoUnH2CRluJVQXbauJnH8SVyIN3H3/gAAAAAZikKZgCYRl+cPKStNTt0rKdBHpdHGxav1W3lNyngz3Q6GgBcsEjE1smeQbV2DKi1a3C0SG7pHFBb58BpR1gE0n0qLcwcK4/jvudnpyo91TfD7wQAAADAdKFgBoBpcLTnuLYdfl5fdBySJF238CrdXXmb8tPyHE4GAOdmcDik1s7BsZXIXQPRQrlzQG1dgwpHTl2F7PW4VZCTqqqSbBXkpKkwJ00FOWkqyE3TRVX56ukacOCdAAAAAJgJFMwAcAHaBtr1zJEX9W7zB5Kkixcs0+aqO1QaKHE2GACchm3b6uobHjfGYmQVcmvnoLr7hic9LjPNp7KiQLQ4zklTQU7qaJGcE0iR+zQjLFL9XvUk8g0BAAAAcBQFMwCch57hXr1Q94r2NLypsB3WkkCJNlfdqYsWLHU6GgAoGIqorWsgbh7y4LgyeTgUOeUYt8ul/OxUlZbnqiA3fVyBXJCTprQUftsIAAAA4FT8SQEAzsFgaEivHntdLx99TUPhYeWn5WlT5W26uvAKuV1up+MBSBK2bat3IKjWzkG1dPZHC+S4ecidPUOa7HZ6aSkeFeWlj42xyE0b/XlBVoo8bq5jAAAAAM4NBTMATEE4Eta+E29rR91L6hnuVcCXqc1Vd2rNohXyurmUAph+4UhE7d1D0VXHHfFjLKJfA0PhU45xScrNStGy0pxx5XFBTpoKc9OUkeqV6zSjLAAAAADgfNCKAMAZ2Lat91s/1vaa59U60C6/x687K27RzaU3KNWb6nQ8AHPcwFBo0pvptXQOqL1rSBH71HXIfq87OraidKw4LshJVUFOmvKzU+Xzehx4JwAAAACSFQUzAJzGwY7D2nr4edX3HJPb5da6xdfr9vKbleUPOB0NwBwRsW119gxNWH08OHqDvd6B4KTHZWX4Vbkoa7Q4HiuS05Sd4WcVMgAAAIBZg4IZACY43nNC22qe12cnLUnStYVXamPlbSpMz3c4GYDZaDgYVmvX4KRjLFo7BxUKn3pDPY/bpfycNJUXB8ZGWMTdUC/FzypkAAAAAHMDBTMAxLQPnNQzR3bq3eb3ZcuWya3Wlqo7tSRrsdPRADjItm319AfHiuMJRXJn7/Ckx2WkerW4IGPc6uORIjk3kCK3m1XIAAAAAOY+CmYASa93uE8v1L+iPcffUMgOqzRzkTZX36mLFyxzOhqAGRIKR9TePXEV8uDobOSh4UluqOeS8rJSdXFZbqw8TlVhbvroWIuMVJ8D7wQAAAAAZhYFM4CkNRQe1q5je/RS/WsaDA8qL3WB7q68TdcuvFJul9vpeACmWf9gMK447ldr5+DoKIv27kFNcj89pfg8426kNzrGIjdNeVmp8nq4VgAAAABIbhTMAJJOOBLW/sZ3tKP2JXUP9yjTl6EHKjdrbclKed1cFoG5KhKxdbJncFxxPHIzvdbOAfUNhiY9LifTr6Ul2aPFcfw85EC6jxvqAQAAAMAZ0KQASBq2beuD1k+0/cjzaulvk9/j1x3lX9LNS25UmjfV6XgApmBoODxWHsd/7xhQW9egwpFTlyF7PW4V5KSqqiR73Arkgpw0FWSnyu/jhnoAAAAAcL4omAEkhUMdNXq6Zofqu4/J7XLrxpLVur38S8pOCTgdDUAc27bV1Td8yurj1s5BtXQOqLtv8hvqZab5VFYUGL2RXvw4i5xAitysQgYAAACAhKBgBjCvNfQ2alvN8/q0/QtJ0tWFV2hT5W0qTC9wOBmQvIKhiNq6BkZHWYwvkgc0HIqccozH7VJeVqpKy3NVELuR3uhq5Jw0paXwWxoAAAAAcAJ/GgMwL7UPdOi52p16u+k92bK1NKdSW6rvVHnWEqejAfOebdvqGwyNK49bOgfUFvve0T2kSe6np7QUj4ry0k8ZY1GYk6YFWSnyuLmhHgAAAADMNhTMAOaV3mCfXqx7Va8f36+QHVZJZrE2V92pSxYs40ZdwDQKRyI62T00Oge5tSN+LvKgBoZOvaGeS1JuVorMkhzlx91IrzBWJGekevnvFAAAAADmGApmAPPCcHhYu47t1c763RoMD2pBaq7urrxN1y28Sm4Xqx6BCxEMhXW0pVd1jT2qbexWbWO3WjoGJr2hnt/rjq4+Ls0ZLY5HZiLnZ6fJ5+W/RwAAAACYTyiYAcxp4UhYbza+q+dqX1LXcLcyfOm6r/Ju3VCyWj43lzjgXIUjEZ1o61dtY7fqGrtV29ij462948rkVL9H5cWBcTOQR8rk7Aw/q5ABAAAAIInQvgCYk2zb1odtn2p7zfNq7m+Vz+3T7WU36Utl65TmTXM6HjAn2Latlo6B2KrkHtU2detoc4+Gg2M32fN63CovCqi8OEsVxQFVFGdp4YJ0uSmRAQAAAACiYAYwBx3urNXWwztU210vt8uttYtW6o6KLyknJdvpaMCsZdu2OnqGVNvYo7qm7tgK5R71x81KdrtcKinIUEVxrFAuylJJQYa8HsZaAAAAAAAmR8EMYM440duk7Uee18dtn0uSriq4XJsqb9PCjEKHkwGzT+9AcHRe8sjs5K6+4XH7LMxN0xVVeaoozlJFcZZKF2YqxedxKDEAAAAAYC6iYAYw63UMdurZ2p16q/GAbNmqzqnQlqo7VZFd5nQ0YFYYHA6pvqknOuYiViq3dQ2O2yc3kKJrlhXErU4OKD3V51BiAAAAAMB8QcEMYNbqC/ZrZ/0u7T6+T6FISIsyirS56g5dmncRNxFD0gqGIjre2jtudfKJ9j7ZY/fgU2aaT5dVLlBFUVZsdXJA2ZkpzoUGAAAAAMxbFMwAZp3hcFCvHd+nF+t3aSA0oNyUHN1deZuWF10tt4tZsEgekYitE+1948ZcHGvpVTgy1ian+D1atjhHFcVZKo/dhC8/O5UPYQAAAAAAM4KCGcCsEY6E9VbTe3qudqc6h7qU4U3XvdUbdWPJavk8/FV+zG+2bau1c2B0zEVdY7fqm3s1FAyP7uP1uLRkYebozOTy4iwVL0iX202ZDAAAAABwBgUzAMfZtq2P2z7TtiMvqKmvWT63T7eWbdAtS9Yr3ZfmdDwgITp6hlTX2K3apm7VNvaorrFbfYOh0eddLmlRfkZszEV0bnJpYaa8HlbxAwAAAABmDwpmAI6q6azT1podOtJVJ5dcWrNohe6suEU5KdlORwOmTe9AUHVxRXJtY7c6e4fH7VOYk6ZLKxaMrk5esjBTqX7+Nw0AAAAAmN34kysARzT2NWt7zQv6qO1TSdKV+ZdqU9XtKspY6HAy4MIMDYdV3xwrkpui4y5aOgbG7ZOT6dfVS/NVHrsBX3lRljLTGAMDAAAAAJh7KJgBzKiOwU7tqH1JbzS+K1u2qrLLtaX6TlVmlzsdDThnoXBEx1t7x81Nbmjrkz12Dz5lpHpjK5MDqiiKzk3ODaQ4FxoAAAAAgGlEwQxgRvQH+7Wzfrd2H9+rYCSkooyF2lJ1hy7Lu1guFzcow+wXidhqPNk/OuKitrFHx1p6FQpHRvfx+9yqLsmO3YAvoIriLBXmpPFrHAAAAAAwb1EwA0ioYDio1xr268W6V9UfGlBOSrY2VtyqlcXXyu3iZmWYnWzbVlvXYGxVcmx1cnOPhobDo/t43C4tLsyMzkwuipbJxfnp8rj5dQ0AAAAASB4UzAASImJH9FbTe3ruyE51DHUq3Zume6rv0o0l18vvYdYsZpeu3qHRMRe1TdFSuXcgOPq8S1JxfoYqigKxuclZKi3MkM/rcS40AAAAAACzAAUzgGll27Y+af9c22qeV2Nfs7xur25Zsl63lq1Xui/d6XiA+gdDqmvqHlud3NStk91D4/bJz07VxWW50dXJxQEtWRhQWgr/ywQAAAAAYKKE/mnZGPNjSask2ZJ+37Ksd+Ke+6akX5cUlvSuZVnfOtsxAGa3I1312np4h2q6auWSS6uLl+uuiluUm5rjdDQkqeFgWEebe0dXJtc29qj5ZP+4fbIy/LqyKi9aJi/KUnlRQIF0v0OJAQAAAACYWxJWMBtj1klaalnWamPMJZJ+IWll7LksSX8kqdqyrJAxZqcxZpWklNMdA2D2aupr0fYjL+jD1k8kSZfnX6JNlbdrUWaRw8mQTELhiBpa+2IjLqJlckNrnyK2PbpPWop33MrkiuIs5QZSuAkfAAAAAADnKZErmG+WtFWSLMv6zBiTa4zJsiyrW9Jw7CvTGNMrKV3SSUVXNJ/uGACzTOdQl3bUvqQ3Gt9VxI6oMrtMm6vuVHVOhdPRMM9FbFvNJ/ujK5Mbe1TX2K2jLb0KhiKj+/i9blUuylJ5rEiuKM5SYW6a3JTJAAAAAABMm0QWzEWSDsQ9bo5t67Ysa9AY8z1JRyT1S/qlZVkHjTGnPeZ0L5Kbmy5vkt5kqaAg4HQEJKm+4X5t+2Kndhx8VcPhoEoCRfrVK7foukVXsBJ0Hpht1xbbttXaMaBDxzp16FiHDh3r1OHjneofDI3u43G7VFacpaWlOVpamqtlS3K0ZGFAHo/bweQARsy26wqAuY/rCoBE4NoCnJ9EFswTWyaXonOVR0Zk/KmkZYqWx68aY6480zGn09HRf6an562CgoBaW3ucjoEkEwwH9XrDG3qx7lX1hfqV7c/SA0s3a2XRtfK4PWpr63U6Ii7QbLi2dPcNx1Ymd6uuKbo6ubs/OG6fogXpurIqf3TMRWlhpvy+8R82njzZN5OxAZzGbLiuAJhfuK4ASASuLcDZne5DmEQWzA2Krj4esUhSU+zniyUdsSyrTZKMMXskXXuWYwA4JGJH9E7T+3rmyIvqGOpUmjdVm6vu0PrFa+T3cDM0nL+BodBoiTwy7qK9e3DcPnlZKbrWFETHXBQFVFaUpfTUhN6jFgAAAAAATFEi/4S+U9L3JP3UGHO1pBOWZY18FFQn6WJjTJqkQUnXSdoh6YszHANghtm2rc9OWtpW87waehvldXt185IbdVvZTcrwpTsdD3NMMBTW0ebesbnJTd1qau8f99dUAuk+XVGVp/KisbnJWRl8iAEAAAAAwGyVsILZsqz9xpgDxpj9kiKSvmmMeVhSl2VZTxtjfiRpl6SQpP2WZe2RpInHJCofgDOr6z6qrYd36FDnEbnk0qqi63RX5S1akJrrdDTMAeFIRA2tfapr6hkdd9HQ2qdwZKxOTvV7ZJbkjBbJ5cUB5WWlMscbAAAAAIA5xGXbZxxxPOu1tvbM7TdwnpgNhERp7m/VMzUv6P3WjyVJl+VdrE1Vt6sks9jhZJgJ53Ntidi2WjoGxuYmN/boaHOPhkOR0X28HrfKFmaqvDhrdG7ywgXpclMmA/Mev2cBMN24rgBIBK4twNkVFAQm/UM8QywBSJK6hrq1o+5l7T/xtiJ2RBVZS7S56k4tza10OhpmEdu21dEzNDrmYuRGfANDodF93C6XFuVnjBbJFcVZKinIkNfjdjA5AAAAAABIBApmIMkNhAb18tHX9OrR1zUcCWpheoE2Vd2hK/MvZVQB1DsQHLcyubaxW119w+P2WZibpiur8kZXJy9ZGFCKz+NQYgAAAAAAMJMomIEkFYyEtLfhTb1Q94p6g33K9gd0f8UmrSq+Th435WAyGhwO6eOaNn3wefNoqdzWNThun9xAiq5ZVqCK4oDKi7NUXhRQRqrPocQAAAAAAMBpFMxAkonYEb3b/IGePfKi2gc7lOpJ1abK27WhdK38Hr/T8eCA7r5hvfDWUb36/nENB8fmJmem+XRZ5QJVFGXFRl0ElJ2Z4mBSAAAAAAAw21AwA0nCtm19fvKgttbsUENvo7wuj24qvUG3ld+kTF+G0/HggK7eIT3/1lHtfr9Bw6GIcgMpuvP6xSrKSVVFcZbys1MZkwIAAAAAAM6IghlIAvXdx7S15nkd7Dgsl1xaUXSNNlbcqry0BU5HgwMmK5YfXF2mG64o1qLiHO6cDAAAAAAApoyCGZjH2gc6tLXmOb3X8pEk6ZI8o82Vd2hxYJHDyeCEzt4h7XizXq99cELBUEQLslJ016oyrb1ikXxet9PxAAAAAADAHETBDMxDoUhIrxx9Xc/XvaJgJKiyQKm2VN+hZbnVTkeDAzp6xorlUDiivKwU3bW6XGsuL6ZYBgAAAAAAF4SCGZhnvjh5SI8d3Krm/lYFfJn6FXOvVhRdwyzdJHSye1A73qzX6x82KhSOKD87VXetLtOay4vl9VAsAwAAAACAC0fBDMwTnUNdeurQszrQ8qFccmnd4uu1seI2pfvSnI6GGXaye1DPvVmvPR+eUChsKz87VRuvL9f1lxVRLAMAAAAAgGlFwQzMceFIWLuO79WO2pc0FB5WedYSPWS2aElgsdPRMMPau8aK5XDEVkFOqjauLtdqimUAAAAAAJAgFMzAHHao44geO7hVJ/qalOFL131L79bq4uVyuygTk0lb14Cee6Neez9qVDhiqzAnTRuvL9eqSxdSLAMAAAAAgISiYAbmoO7hHj19+Dm93fSeXHJpzaIV2lR1hzJ9GU5Hwwxq6xzQs2/Ua9/H0WJ5Ye5YsexxUywDAAAAAIDEo2AG5pCIHdHrDW/o2SMvaiA0qNJAiR5ado8qspc4HQ0zqKVzQM/tr9P+T5qixfKCdG26vlwrLimkWAYAAAAAADOKghmYI2q76vWo9bSO9Z5QmjdNDy3borUlqxiHkURaOvr17P567f+kSRHbVtGCdN29plwrL14ot9vldDwAAAAAAJCEKJiBWa53uE/bap7X/sa3JUkri67VPdV3KeDPdDgZZkpzR7+e3VenNz5tVsS2VZwXLZZXXESxDAAAAAAAnEXBDMxSETui/Sfe1vaaF9QX6teijCI9ZO5RdU6F09EwQ5pP9uuZ/XV649Mm2ba0KD9Dm9aU6zpTSLEMAAAAAABmBQpmYBY62n1cvzz4tOq7jynVk6L7qjdq3eI18rg9TkfDDGhs79Oz++v05mfNsm2pJD9Dm9ZW6FpTILeLYhkAAAAAAMweFMzALNIf7NczR17UnoY3ZcvWdQuv0j3VdyknJdvpaJgBje19emZfnd76PFosLy7I0KY1FbqGYhkAAAAAAMxSFMzALGDbtt5qOqCnDz+n3mCfFqYX6qFlW2QWVDsdDTOgoa1Pz+yr1Tuft8iWVFqYqU1rynX1MoplAAAAAAAwu1EwAw5r6G3Uo9bTqumqk9/t0+aqO3RT6Q3yuvnPc75raO3VM/vrRovlJYWZ2rS2QlctzadYBgAAAAAAcwINFuCQgdCgnqvdqdeO71fEjuiqgst139KNWpCa63Q0JNjxll5t31+nA1/EiuWFmdq8tkJXVefLRbEMAAAAAADmEApmYIbZtq0DzR/oqcPPqmu4RwVpeXpg2RZdmmecjoYEO9bSq+37anXAapUklRUFtHlNha6szqNYBgAAAAAAcxIFMzCDmvqa9ai1VQc7a+Rze7Wx4lZ9ack6+Tw+p6MhgY4292j7vjq9dzBaLFcUB7RpTYWuqKJYBgAAAAAAcxsFMzADBkNDeqHuFb1y7HVF7Iguy7tYDyzbpPy0PKejIYHqm3q0fV+t3j/UJkmqXJSlTWsqdHnlAoplAAAAAAAwL1AwAwlk27Y+aP1ETx56Rh1DnVqQmqsHlm7SFQWXOh0NCVTX1K3te+v0weFosVy1KEub11bo0gqKZQAAAAAAML9QMAMJ0tLfqscObtPnJw/K6/Lo9vKbdVvZBvk9fqejIUFqG7u1fW+tPqxplyRVl2Rr09pyXVpOsQwAAAAAAOYnCmZgmg2Hg9pZ/6peqt+tkB3WxQuW6YFlm7UwvcDpaEiQIye6tX1frT6KFctLF2dr09oKXVKWS7EMAAAAAADmNQpmYBp93PaZHj+4Te2DHcpJydZ9S+/W1QWXUzLOUzUnurR9b50+PhItlpeV5mjzmnJdRLEMAAAAAACSBAUzMA3aBk7qiUPb9HHb53K73PrSknW6o/xLSvWmOB0NCXC4oUvb99bqk9qTkiRTmqPNayt0UVmuw8kAAAAAAABmFgUzcAGCkZBern9NL9a/omAkpKU5lXpw2RYtyixyOhoS4NDxTm3fW6tP6zokSRctiRbLZgnFMgAAAAAASE4UzMB5+rz9oB47uFUtA23K8gf0a9Ubdd3CqxiNMA8dPNapbXtr9Xl9tFi+uCxXm9dWaFlpjrPBAAAAAAAAHEbBDJyjjsFOPXnoGb3f+rFccmnD4rW6q/IWpXnTnI6GaWYd7dD2fXWjxfIl5bnatIZiGQAAAAAAYAQFMzBFoUhIu47t1Y66lzUcHlZldpkeWnaPFgcWOR0N0+yL+g5t31erL452SpIurVigzWsqVL0429lgAAAAAAAAswwFMzAFBztq9Kj1tJr6W5Tpy9CDSzdrZfG1crvcTkfDNLFtW18cjY7COHisU5J0WeUCbVpToeoSimUAAAAAAIDJUDADZ9A11K2nDj+rd5s/kEsurS1ZpU2VtyvDl+50NEwT27b1eX2Htu+t1cHjXZKkK6rydPeaclUtolgGAAAAAAA4EwpmYBLhSFivN7yhZ4/s1GB4UEsCi/Vlc4/KskqdjoZpYtu2Pqvr0LZ9tTocVyxvWlOhykVZDqcDAAAAAACYGyiYgQmOdNXpl9bTauhtVLo3TV8292rNohWMw5gnbNvWp3UntW1vrWoauiVJV1Xn6+415aooplgGAAAAAAA4FxTMQEzPcK+21uzQm43vSpJWFy/X5qo7FPBnOpwM08G2bX1Se1Lb99aq5kS0WL56ab42ralQWVHA4XQAAAAAAABzEwUzkl7Ejmhvw1vafuQFDYQGVJJZrC+be1SZXe50NEwD27b18ZF2bdtbp9rGaLF8zbICbVpTriULKZYBAAAAAAAuBAUzklp99zH90npaR3uOK9WTqvuXbtKNJavlcXucjoYLZNu2Pqxp1zP7alXb2CNJunZZge6mWAYAAAAAAJg2FMxISn3Bfm2veV77TrwtW7aWL7xG91TfpewUise5zrZtfXi4Xdv21aq+KVosX2cKdPeaCpUWMu4EAAAAAABgOlEwI6lE7IjebDygbTU71BvsU3HGQj20bIuW5lY5HQ0XyLZtfXCoTdv31am+uUcuScsvKtTda8q1uIBiGQAAAAAAIBEomJE0jvWc0KPW06rtrpff49c91Xdpw+K1jMOY4yK2rfcPtumZfbU62tIrl6QVFxfq7uvLVUKxDAAAAAAAkFAUzJj3BkIDeubITr1+fL9s2bqm8ArdW71Ruak5TkfDBYjYtt6zWrV9X52Ot0aL5ZWXLNTG68tVkp/hdDwAAAAAAICkQMGMecu2bb3T/L6eOvyseoZ7VZierweXbdHFC5Y5HQ0XYKxYrtXx1j65XNKqSxfq7uvLVZxHsQwAAAAAADCTElowG2N+LGmVJFvS71uW9U5se4mkf4vbtVLStyVtl/QvkhZI8kv6nmVZLyYyI+anE71NeuzgVh3qPCKf26e7K2/XzUtulM/NZypzVcS29e4XLXpmf50aYsXy6kuLtPH6MoplAAAAAAAAhySsbTPGrJO01LKs1caYSyT9QtJKSbIsq0HS+th+Xkm7FS2XH44+bf2JMWaRpFclXZSojJh/BkOD2lH7snYd36uIHdEV+Zfq/qV3Ky9tgdPRcJ4iEVvvxIrlE219crtcWnNZkTZeX66FC9KdjgcAAAAAAJDUErmc82ZJWyXJsqzPjDG5xpgsy7K6J+z3sKQnLcvqNca0Sboitj1XUlsC82EesW1b77V8pKcOP6vOoS7lpS7Qg8s267L8i52OhvMUidh6+/NmPbO/To3t/dFi+fJYsZxLsQwAAAAAADAbJLJgLpJ0IO5xc2zbxIL5q5JulSTLsn5pjHnYGHNY0YL5rrO9SG5uurxez/QknmMKCgJOR5gVTnQ36R/fe0wfNX8un9ur+y+9S1suulV+r9/paDgP4YitPe8f1y9fOqiG1l653S7dsmKJHrh5mYq5ed+M4NoCYLpxXQEw3biuAEgEri3A+Ulkweya5LEdv8EYs1rSFyOrmo0xvy7pqGVZtxtjrpT0c0nLz/QiHR3905d4DikoCKi1tcfpGI4aDg/rhbpX9fLR1xS2w7okz+iBpZtVmJ6vro4hSUNOR8Q5CEcieuuzZj2zv17NJ/vlcbt045XFumt1uQpy0iQ7kvS/5mcC1xYA043rCoDpxnUFQCJwbQHO7nQfwiSyYG5QdMXyiEWSmibss1HSy3GP10h6UZIsy/rQGFNijPFalhVKYE7MMbZt66O2z/TEoe06Odih3JQc3b9sk67Mv1Qu18TPNTDbhSMRvflpdBRGS8eAPG6X1l21SHetKlN+TprT8QAAAAAAAHAGiSyYd0r6nqSfGmOulnTCsqyJHwUtl/TLuMeHFb0R4JPGmDJJvZTLiNc20K7HDm7Tp+1fyOPy6NayDbq9/GaleBiHMdeEwhG98WmTnttfr5bOaLG8/qpFunN1mfKzKZYBAAAAAADmgoQVzJZl7TfGHDDG7JcUkfRNY8zDkrosy3o6tluxpJa4w34q6R+NMa/Fsv1uovJhbgmGg9p5dLd21u9SKBLSstxqPbRsi4oyCp2OhnMUCkf0xidNevaNOrV2DsrrcWnD1SW6c1WZ8rJTnY4HAAAAAACAc+Cybfvse81ira0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      "text/plain": [
       "<Figure size 1440x1080 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "f,ax = plt.subplots(2,1,figsize=(20,15))\n",
    "\n",
    "ax[0].plot(history.history['accuracy'])\n",
    "ax[0].plot(history.history['val_accuracy'])\n",
    "ax[0].set_title('Model Accuracy')\n",
    "ax[0].set_ylabel('Accuracy')\n",
    "ax[0].set_xlabel('Epochs')\n",
    "ax[0].legend(['LSTM_train', 'LSTM_val'], loc='upper left')\n",
    "\n",
    "\n",
    "ax[1].plot(history.history['loss'])\n",
    "ax[1].plot(history.history['val_loss'])\n",
    "ax[1].set_title('Model Loss')\n",
    "ax[1].set_ylabel('Loss')\n",
    "ax[1].set_xlabel('Epochs')\n",
    "ax[1].legend(['train', 'val'], loc = 'upper left')\n",
    "\n",
    "f.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.095022,
     "end_time": "2021-06-01T03:37:58.028943",
     "exception": false,
     "start_time": "2021-06-01T03:37:57.933921",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# 7. Submission\n",
    "* Submit the predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:58.230283Z",
     "iopub.status.busy": "2021-06-01T03:37:58.229772Z",
     "iopub.status.idle": "2021-06-01T03:37:58.241013Z",
     "shell.execute_reply": "2021-06-01T03:37:58.239615Z"
    },
    "papermill": {
     "duration": 0.116569,
     "end_time": "2021-06-01T03:37:58.241134",
     "exception": false,
     "start_time": "2021-06-01T03:37:58.124565",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sample = pd.read_csv('/kaggle/input/nlp-getting-started/sample_submission.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:58.443857Z",
     "iopub.status.busy": "2021-06-01T03:37:58.443095Z",
     "iopub.status.idle": "2021-06-01T03:37:58.448142Z",
     "shell.execute_reply": "2021-06-01T03:37:58.448652Z"
    },
    "papermill": {
     "duration": 0.111373,
     "end_time": "2021-06-01T03:37:58.448826",
     "exception": false,
     "start_time": "2021-06-01T03:37:58.337453",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
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      "text/plain": [
       "   id  target\n",
       "0   0       0\n",
       "1   2       0\n",
       "2   3       0\n",
       "3   9       0\n",
       "4  11       0"
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     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:58.652656Z",
     "iopub.status.busy": "2021-06-01T03:37:58.652141Z",
     "iopub.status.idle": "2021-06-01T03:37:58.670164Z",
     "shell.execute_reply": "2021-06-01T03:37:58.668745Z"
    },
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     "start_time": "2021-06-01T03:37:58.545800",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test = pd.read_csv('/kaggle/input/nlp-getting-started/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:58.890587Z",
     "iopub.status.busy": "2021-06-01T03:37:58.889778Z",
     "iopub.status.idle": "2021-06-01T03:37:58.893429Z",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Typhoon Soudelor kills 28 in China and Taiwan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   id keyword location                                               text\n",
       "0   0     NaN      NaN                 Just happened a terrible car crash\n",
       "1   2     NaN      NaN  Heard about #earthquake is different cities, s...\n",
       "2   3     NaN      NaN  there is a forest fire at spot pond, geese are...\n",
       "3   9     NaN      NaN           Apocalypse lighting. #Spokane #wildfires\n",
       "4  11     NaN      NaN      Typhoon Soudelor kills 28 in China and Taiwan"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:59.100829Z",
     "iopub.status.busy": "2021-06-01T03:37:59.100074Z",
     "iopub.status.idle": "2021-06-01T03:37:59.103707Z",
     "shell.execute_reply": "2021-06-01T03:37:59.103302Z"
    },
    "papermill": {
     "duration": 0.111071,
     "end_time": "2021-06-01T03:37:59.103819",
     "exception": false,
     "start_time": "2021-06-01T03:37:58.992748",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Just happened a terrible car crash</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Heard about #earthquake is different cities, s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>there is a forest fire at spot pond, geese are...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Apocalypse lighting. #Spokane #wildfires</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Typhoon Soudelor kills 28 in China and Taiwan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>We're shaking...It's an earthquake</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>They'd probably still show more life than Arse...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Hey! How are you?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>What a nice hat?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Fuck off!</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                text\n",
       "0                 Just happened a terrible car crash\n",
       "1  Heard about #earthquake is different cities, s...\n",
       "2  there is a forest fire at spot pond, geese are...\n",
       "3           Apocalypse lighting. #Spokane #wildfires\n",
       "4      Typhoon Soudelor kills 28 in China and Taiwan\n",
       "5                 We're shaking...It's an earthquake\n",
       "6  They'd probably still show more life than Arse...\n",
       "7                                  Hey! How are you?\n",
       "8                                   What a nice hat?\n",
       "9                                          Fuck off!"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.drop(['keyword','id','location',],axis=1,inplace=True)\n",
    "test.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:59.343566Z",
     "iopub.status.busy": "2021-06-01T03:37:59.338520Z",
     "iopub.status.idle": "2021-06-01T03:37:59.481909Z",
     "shell.execute_reply": "2021-06-01T03:37:59.481429Z"
    },
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     "duration": 0.278875,
     "end_time": "2021-06-01T03:37:59.482032",
     "exception": false,
     "start_time": "2021-06-01T03:37:59.203157",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test.text = test.text.apply(lambda x: preprocess(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:59.682318Z",
     "iopub.status.busy": "2021-06-01T03:37:59.681591Z",
     "iopub.status.idle": "2021-06-01T03:37:59.685324Z",
     "shell.execute_reply": "2021-06-01T03:37:59.684787Z"
    },
    "papermill": {
     "duration": 0.10544,
     "end_time": "2021-06-01T03:37:59.685460",
     "exception": false,
     "start_time": "2021-06-01T03:37:59.580020",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3263, 1)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:37:59.904636Z",
     "iopub.status.busy": "2021-06-01T03:37:59.899511Z",
     "iopub.status.idle": "2021-06-01T03:37:59.952604Z",
     "shell.execute_reply": "2021-06-01T03:37:59.952167Z"
    },
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     "duration": 0.168703,
     "end_time": "2021-06-01T03:37:59.952715",
     "exception": false,
     "start_time": "2021-06-01T03:37:59.784012",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test Shape: (3263, 30)\n"
     ]
    }
   ],
   "source": [
    "test = pad_sequences(tokenizer.texts_to_sequences(test.text), maxlen = 30)\n",
    "\n",
    "print(\"test Shape:\",test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:38:00.157128Z",
     "iopub.status.busy": "2021-06-01T03:38:00.156321Z",
     "iopub.status.idle": "2021-06-01T03:38:01.881633Z",
     "shell.execute_reply": "2021-06-01T03:38:01.881139Z"
    },
    "papermill": {
     "duration": 1.829877,
     "end_time": "2021-06-01T03:38:01.881762",
     "exception": false,
     "start_time": "2021-06-01T03:38:00.051885",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 1, 1, 1, 1, 1, 0, 0, 0, 0]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction = model.predict(test)\n",
    "prediction = list(1 if x>0.5 else 0 for x in list(prediction))\n",
    "prediction[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:38:02.089176Z",
     "iopub.status.busy": "2021-06-01T03:38:02.088498Z",
     "iopub.status.idle": "2021-06-01T03:38:02.091854Z",
     "shell.execute_reply": "2021-06-01T03:38:02.092231Z"
    },
    "papermill": {
     "duration": 0.110934,
     "end_time": "2021-06-01T03:38:02.092372",
     "exception": false,
     "start_time": "2021-06-01T03:38:01.981438",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    2103\n",
       "1    1160\n",
       "Name: target, dtype: int64"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample['target'] = prediction\n",
    "sample['target'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-01T03:38:02.295972Z",
     "iopub.status.busy": "2021-06-01T03:38:02.295453Z",
     "iopub.status.idle": "2021-06-01T03:38:02.406177Z",
     "shell.execute_reply": "2021-06-01T03:38:02.405332Z"
    },
    "papermill": {
     "duration": 0.213549,
     "end_time": "2021-06-01T03:38:02.406308",
     "exception": false,
     "start_time": "2021-06-01T03:38:02.192759",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sample.to_csv('submission.csv',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "papermill": {
     "duration": 0.097525,
     "end_time": "2021-06-01T03:38:02.603591",
     "exception": false,
     "start_time": "2021-06-01T03:38:02.506066",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "##### reference \n",
    "* https://www.kaggle.com/mnavaidd/tweet-classification-using-lstm-bert/notebook?select=glove.6B.zip\n",
    "* https://www.kaggle.com/gunesevitan/nlp-with-disaster-tweets-eda-cleaning-and-bert\n",
    "\n",
    "###  If this notebook is useful for your kaggling, \"UPVOTE\" for it 👀\n",
    "#### THX to Reading My Notebook🌈"
   ]
  }
 ],
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