python 创建多层感知机，神经网络

# 多层感知器, 神经网络
from sklearn.neural_network import MLPRegressor# 设置交叉验证集的折数
# 时间序列分割
from sklearn.model_selection import TimeSeriesSplit
tscv = TimeSeriesSplit(max_train_size=None, n_splits=13)
def cv_mae_(model, train_X, train_y):val_loss = -cross_val_score(model, train_X, train_y, scoring="neg_mean_absolute_error", cv=tscv)print('val loss is: {0}'.format(val_loss))import matplotlib.pyplot as pltplt.plot(val_loss, marker = 'o')plt.show()cv_mae = np.mean(-cross_val_score(model, train_X, train_y, scoring="neg_mean_absolute_error", cv = tscv))return cv_maedef build_model(train_X, train_y):init_params = {# 三层，神经元个数依次是 26 、6、10'hidden_layer_sizes': (26, 6, 10),'solver': 'lbfgs','max_iter': 20000,'early_stopping': False,'shuffle': False,'verbose': True,'random_state': 1,}mult_mlp = MLPRegressor(**init_params)cv_mae_mlp = cv_mae_(mult_mlp, train_X, train_y)mult_mlp = mult_mlp.fit(train_X, train_y)