util.py 文件源码

def gradient_boosting_classify(my_train_data, my_train_label, my_test_data, estimators):
    clf = GradientBoostingClassifier(n_estimators=estimators)
    scores = cross_validation.cross_val_score(clf, my_train_data, my_train_label, cv=5)
    print("gradient boosting(%d) accuracy: %0.3f (+/- %0.3f)" % (estimators, scores.mean(), scores.std() * 2))
    clf.fit(my_train_data, my_train_label)
    my_test_label = clf.predict(my_test_data)
    file_name = "gradient_boosting_%d.csv" % estimators
    save_data(my_test_label, file_name)