main.py 文件源码

def mlp_regression(parameter_array):
    layer_value = parameter_array[0]
    second_layer_value = parameter_array[1]
    learning_rate = parameter_array[2]
    return neural_network.MLPRegressor(hidden_layer_sizes=(layer_value,second_layer_value), activation='identity', solver='adam', alpha=1,
                                        batch_size='auto', learning_rate='constant', learning_rate_init=learning_rate, power_t=0.5,
                                        max_iter=200, shuffle=True, random_state=None, tol=0.0001, verbose=False, warm_start=False,
                                        momentum=0.9, nesterovs_momentum=True, early_stopping=False, validation_fraction=0.1, beta_1=0.9, beta_2=0.999, epsilon=1e-08)

#Dictionary with the name of the algorithm as the key and the function as the value