#!/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, collections
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()

#features_train = features_train[:len(features_train)/100] 
#labels_train = labels_train[:len(labels_train)/100]



#########################################################
from sklearn.svm import SVC

classifier = SVC(kernel='rbf', C=10000)

t0 = time()

classifier.fit(features_train, labels_train)

print "Training time: ", (time() - t0), "s"

#########################################################

t0 = time()

pred = classifier.predict(features_test)

print "Prediction time: ", (time() - t0), "s"

#########################################################
print collections.Counter(pred)
print classifier.score(features_test, labels_test)
