common_defs.py 文件源码

def train_and_eval_sklearn_regressor( clf, data ):

    x_train = data['x_train']
    y_train = data['y_train']

    x_test = data['x_test']
    y_test = data['y_test'] 

    clf.fit( x_train, y_train ) 
    p = clf.predict( x_train )

    mse = MSE( y_train, p )
    rmse = sqrt( mse )
    mae = MAE( y_train, p )


    print "\n# training | RMSE: {:.4f}, MAE: {:.4f}".format( rmse, mae )

    #

    p = clf.predict( x_test )

    mse = MSE( y_test, p )
    rmse = sqrt( mse )
    mae = MAE( y_test, p )

    print "# testing  | RMSE: {:.4f}, MAE: {:.4f}".format( rmse, mae )  

    return { 'loss': rmse, 'rmse': rmse, 'mae': mae }