knock78.py 文件源码

def cv(feature_dict, feature, polarity, folds):
    kfold = KFold(len(polarity), n_folds = folds)
    count, f1, recall, precision, accuracy = 0, 0, 0, 0, 0
    for train, test in kfold:
        LR = LogisticRegression()
        count += 1
        x = [(feature[i]) for i in train]
        y = [(polarity[i])for i in train]
        LR.fit(scipy.sparse.vstack(x), (y))

        test_label = []
        answer_label = [(polarity[j]) for j in test]
        for j in test:
            query = feature[j]
            result = -1 if query.shape[1] != len(feature_dict) else predict(LR, query)
            test_label.append(int(result[0]))
        accuracy += accuracy_score(answer_label, test_label)
        precision += precision_score(answer_label, test_label)
        recall += recall_score(answer_label, test_label)
        f1 += f1_score(answer_label, test_label)
        print('{}_fold finished.'.format(count))
    return accuracy, precision, recall, f1