Model evaluation vs Model validation



Is there a difference between Model evaluation and Model Validation?

Does ConfusionMatrix, AUC, Gainlift curve falls under validation or evaluation metrics?


Model evaluation refers to checking the performance of our final predictions on the test dataset.

Model validation generally refers to the hyperparameter tuning of the model on the cross validation set in order to get the best results.

All of these fall under the category of evaluation metrics.

Hope this clears your doubt.