In here i try to predict selling price of used car using XGBoost algorithm, the total of dataset is only 311. for the column are Name, seller type, year, selling price, transmission, km driven, owner.
R2 RESULT :
score = metrics.r2_score(Y_test, y_pred)
print("Training score: ", score)
Training score: 0.5955576270160517
MAE RESULT :
mae = mean_absolute_error(Y_test, y_pred)
MSE AND RMSE RESULT :
ypred = xg.predict(X_test)
mse = mean_squared_error(Y_test, ypred)
print("MSE: %.2f" % mse)
print("RMSE: %.2f" % (mse**(1/2.0)))
What I have tried:
Anyone can explain about the score, is the score perfect or not ?