__init__.py 文件源码

def print_regression_model_summary(prefix, y_test, y_pred, parmsFromNormalization):
    y_test = (y_test*parmsFromNormalization.std*parmsFromNormalization.sqrtx2) + parmsFromNormalization.mean
    y_pred = (y_pred*parmsFromNormalization.std*parmsFromNormalization.sqrtx2) + parmsFromNormalization.mean

    mse = mean_squared_error(y_test, y_pred)
    error_AC, rmsep, mape, rmse = almost_correct_based_accuracy(y_test, y_pred, 10)
    rmsle = calculate_rmsle(y_test, y_pred)
    print ">> %s AC_errorRate=%.1f RMSEP=%.6f MAPE=%6f RMSE=%6f mse=%f rmsle=%.5f" %(prefix, error_AC, rmsep, mape, rmse, mse, rmsle)
    log.write("%s AC_errorRate=%.1f RMSEP=%.6f MAPE=%6f RMSE=%6f mse=%f rmsle=%.5f" %(prefix, error_AC, rmsep, mape, rmse, mse, rmsle))


# Utility function to report best scores