How to Perform Feature Selection with Categorical Data

Feature selection is the process of identifying and selecting a subset of input features that are most relevant to the target variable. Feature selection is often straightforward when working with real-valued data, such as using the Pearson's correlation coefficient, but can be challenging when working with categorical data. The two most commonly used feature selection methods for categorical input data when the target variable is also categorical (e.g. In this tutorial, you will discover how to perform feature selection with categorical input data. How to Perform Feature Selection with Categorical Data Photo by Phil Dolby, some rights reserved. As the basis of this tutorial, we will use the so-called "Breast cancer" dataset that has been widely studied as a machine learning dataset since the 1980s.