Why don’t we tune hyper-parameters using test set and need a separate set like validation set?

We use test set such that we build a model that generalizes well on unseen dataset. If we use test set in tuning for hyper-parameters to select the model, we’re indirectly using test set in training or rather, our model has seen the test set. Hence, it is no longer an unseen dataset but already used to find the right parameters. For additional explanation, please check what is the difference between testing and validation or test set and validation set ?

 

 

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