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 if actual == predicted: true_positives[actual] += 1 confusion_matrix[actual][predicted] += 1