Computational Actuarial Science with R

Chapter 4

Statistical Learning

Arthur Charpentier

Université du Québec á Montrél Montréal, Québec, Canada,

Stéphane Tufféry

ENSAI & Université de Rennes 1 Rennes, France

4.1 Introduction and Motivation

In this chapter, we will describe some techniques to learn from data, and to make a prediction based on a set of features. We will use a training set, where those features were observed, as well as our variable of interest, to build a predictive model. A good model will accurately predict the variable of interest. This is actually a standard procedure in actuarial science, where the variable of interest might be

• Whether an insured will buy additional (optional) coverage, or not
• Whether a claimant will be represented by an attorney, or not (see ...