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Dec 27, 2019 in Data Science
Q: Can you explain the difference between a Validation Set and a Test Set?

1 Answer

Dec 27, 2019

A Validation set can be considered as a part of the training set as it is used for parameter selection and to avoid overfitting of the model being built.

On the other hand, a Test Set is used for testing or evaluating the performance of a trained machine learning model.

In simple terms, the differences can be summarized as; training set is to fit the parameters i.e. weights and test set is to assess the performance of the model i.e. evaluating the predictive power and generalization.

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