part 6

multinomialNaiveBayes_part6.py

# return the class with highest score for sentence
def classify(sentence):
    high_class = None
    high_score = 0
    # loop through our classes
    for c in class_words.keys():
        # calculate score of sentence for each class
        score = calculate_class_score_commonality(sentence, c, show_details=False)
        # keep track of highest score
        if score > high_score:
            high_class = c
            high_score = score

    return high_class, high_score