Explainable AI Recipes: Implement Solutions to Model Explainability and Interpretability with Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

P. MishraExplainable AI Recipes https://doi.org/10.1007/978-1-4842-9029-3_3

3. Explainability for Nonlinear Supervised Models

Pradeepta Mishra¹  

(1)

Bangalore, Karnataka, India

 

In this chapter, we are going to use explainable libraries to explain a regression model and a classification model, while training a nonlinear model. A nonlinear model is something where either the input variables are transformed using nonlinear transformations or the function to model the input and output is nonlinear.

In the pursuit of achieving higher accuracy, input features are modified either by including polynomial features or by including interaction features, such as additive ...