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

1 Answer

0 votes
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.

Click here to read more about Loan/Mortgage
Click here to read more about Insurance