task73.py 文件源码

def task73(features):

    features = numpy.array(features)
    words = list(set(features[:, 1]))

    pos_vec = numpy.zeros(len(words))
    neg_vec = numpy.zeros(len(words))

    for feature in features:
        index = words.index(feature[1])
        if feature[0] == '-1':
            pos_vec[index] += 1
        else:
            neg_vec[index] += 1

    model = linear_model.LogisticRegression()
    model.fit([pos_vec, neg_vec], [1, -1])

    return (words, model)