random_forest.py 文件源码

def regression():
    # Generate a random regression problem
    X, y = make_regression(n_samples=500, n_features=5, n_informative=5,
                           n_targets=1, noise=0.05, random_state=1111,
                           bias=0.5)
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1,
                                                        random_state=1111)

    model = RandomForestRegressor(n_estimators=50, max_depth=10, max_features=3, )
    model.fit(X_train, y_train)
    predictions = model.predict(X_test)
    print('regression, mse: %s'
          % mean_squared_error(y_test.flatten(), predictions.flatten()))