mnist.py 文件源码

def run_example():

    data, target = _get_data()

    n_folds = 5
    accuracy = 0.0

    for (train_idx, test_idx) in KFold(n=len(data), n_folds=n_folds, shuffle=True):

        train_X = data[train_idx]
        train_y = target[train_idx]

        test_X = data[test_idx]
        test_y = target[test_idx]

        model = SGDClassifier()
        model.fit(train_X, train_y)

        predictions = model.predict(test_X)

        accuracy += accuracy_score(predictions, test_y)

    return accuracy / n_folds