nltk Bayes Classifier with real comments

nltk_classifier_comments

#Training part
training = pos[:int((.5)*len(pos))] + neg[:int((.5)*len(neg))]
#this cryptic way to write it's just to select the last half part of the
#data set (above)
#and the first half dataset (below)
test = pos[int((.5)*len(pos)):] + neg[int((.5)*len(neg)):]
counter = 0
test_dataset = []
with open("basic_positive.csv","r") as reader:
    for line in reader:
        test_dataset.append(line)
        counter+=1
        if counter==25:
            break

print(len(test_dataset))
counter= 0
with open("basic_negative.csv","r") as reader:
    for line in reader:
        test_dataset.append(line)
        counter+=1
        if counter==25:
            break
print(len(test_dataset))
#this will be the testdataset


#at the moment stick to the basic Bayes
classifier = NaiveBayesClassifier.train(training)
print("Most informative features...")
print(classifier.show_most_informative_features())