Model Selection using Bias Variance Trade Off

I have a Regression Model with Train MAPE as 6% and Test MAPE as 15%. This appears to me as a clear case of over fitting. But can I still use this model assuming 15% Error is not a bad number after-all. Is this there a flaw in this thinking?

Topic bias variance model-selection machine-learning

Category Data Science

1
answered at

Yes, assuming you haven't overfitted on the test set (which may happen after extensive hyperparameter optimization), you can assume that your model has a MAPE of 15%.

However, if you limit the overfitting, the test performance would probably go down!

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