A way to keep the most useful inputs and drop the rest.
Feature selection is like cleaning out a kitchen junk drawer. Keep the batteries. Toss the mystery keys.
You use it with table data. It cuts noise. It makes models faster. It makes results easier to explain.
Feature-engineering
Feature selection is a key step in feature engineering.
Lasso
Lasso can push weak feature weights to zero.
Regularization
Feature selection often works with regularization to reduce overfitting.
Decision Tree
A decision tree naturally favors more useful features when it splits.