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 input and output data, such as using the Pearson’s correlation coefficient, but can be challenging when working with numerical input data and a categorical […]
The post How to Perform Feature Selection With Numerical Input Data appeared first on Machine Learning Mastery.
Comments
Post a Comment