#!/usr/bin/python

""" 
    This is the code to accompany the Lesson 1 (Naive Bayes) mini-project. 

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

### 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()
clf = GaussianNB()

t0 = time()
clf.fit(features_train, labels_train)
print "training time:", round(time()-t0, 3), "s"

t1 = time()
print accuracy_score(clf.predict(features_test), labels_test) 
print "predicting time:", round(time()-t1, 3), "s"

