This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linea

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simp

Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tib

Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly to model a binary res

Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the conditional distribution of the resp