nb_author_id.py

#!/usr/bin/python

""" 
    Use a Naive Bayes Classifier to identify emails by their authors
    
    authors and labels:
    Sara has label 0
    Chris has label 1
"""
    
import sys
from time import time
sys.path.append("../tools/")
from email_preprocess import preprocess


### features_train and features_test are the features for the training
### and testing datasets, respectively
### labels_train and labels_test are the corresponding item labels
features_train, features_test, labels_train, labels_test = preprocess()





from sklearn.naive_bayes import GaussianNB
clf=GaussianNB()
t0 = time()
clf.fit(features_train,labels_train)
print ("training time:", round(time()-t0, 3), "s")

t0 = time()
pred = clf.predict(features_test)
print ("testing time:", round(time()-t0, 3), "s")

from sklearn.metrics import accuracy_score
accuracy=accuracy_score(labels_test,pred)

print("accuracy is ",accuracy)