text: #!/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
  """
      
  import sys
  from time import time
  sys.path.append("../tools/")
  from email_preprocess import preprocess
  from sklearn.naive_bayes import GaussianNB
  import numpy as np
  
  ### 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()
  
  
  #########################################################
  ### your code goes here ###
  gnb = GaussianNB()
  t0 = time()
  gnb.fit(features_train, labels_train)
  print "training time:", round(time()-t0, 3), "s"
  
  t0 = time()
  y_pred = gnb.predict(features_test)
  print "predict time:", round(time()-t0, 3), "s"
  
  result_array = np.asarray(y_pred) - np.asarray(labels_test)
  target_hit = 0
  for num in result_array:
  	if num == 0:
  		target_hit += 1
  accuracy = float(target_hit)/len(result_array)
  print(accuracy)
  
  #########################################################
  
  
  