Validation applies the model to test data in order to determine whether the model, built on a training set, is generalizable to other data. In particular, it helps to avoid the phenomenon of overfitting, which can occur when the logic of the model fits the build data too well and therefore has little predictive power.
Validation is a process that help to tell how well does a model in terms of test error
Generally, the Build Activity splits the data into two mutually exclusive subsets:
However, if the data is already split into Build and Test subsets, you can specify them.