beg = time.time()
parser_train = DatasetParser("trainingimages.txt","traininglabels.txt")
parser_test = DatasetParser("testimages.txt","testlabels.txt")
train_samples = parser_train.read()
test_samples = parser_test.read()
classifier = NaiveBayes(train_samples,test_samples)
print "Training starts..."
classifier.train()
print "Testing starts..."
predictions = classifier.test()
digit_counts = 10*[0]
digit_predicted_counts = 10*[0]
true_positives = 10*[0]
confusion_matrix = [[0 for x in range(10)] for x in range(10)] ;
for key in predictions:
(predicted,actual) = predictions[key]
digit_counts[actual] += 1
digit_predicted_counts[predicted] += 1
