text: #!/usr/bin/python
  
  """ 
      This is the code to accompany the Lesson 2 (SVM) mini-project.
  
      Use a SVM to identify emails from the Enron corpus by their authors:    
      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()
  
  
  
  #########################################################
  ### your code goes here ###
  from sklearn.svm import SVC
  from sklearn.metrics import accuracy_score
  
  features_train = features_train[:len(features_train)/100] 
  labels_train = labels_train[:len(labels_train)/100] 
  
  clf = SVC(kernel='rbf', C=10000)
  
  t0 = time()
  clf.fit(features_train, labels_train)
  print 'training time =', round(time() - t0, 3), 's'
  
  t0 = time()
  pred = clf.predict(features_test)
  print 'prediction time =', round(time() - t0, 3), 's'
  
  print accuracy_score(labels_test, pred)
  
  #print pred[10], pred[26], pred[50]
  #print (pred == 1).sum()
  #########################################################
  
  
  