Train and Test

Split Data into Training and Test sets and the model is fitted on Training Set. Fitted model is used on Test Set.

For instance we can have 70% Training Data and 30% Test Data. We would train the model on the 70% of Training Data and use the Fitted Model on the 30% Test Data.

This approach can be susceptible to Data Leakage.

For example, finding the best $k$ in $K$ Nearest Neighbours using only Train and Test sets would result in Data Leakage. This is because we are fitting the model to the test set by adjusting $k$.