When we train a machine learning algorithm on any dataset, the data may have features that are not required as they may not be affecting the target variable or there may be redundant features that are giving the same information to the model.
Feature Selection is a method of selecting features that are affecting the target variables and removing the features that are not required.
Methods of Feature Selection
How to Choose a Feature Selection Method
Below is a flow diagram that shows the feature selection method based on the type of feature.
