Contact personalization using a score understanding method

Abstract

This paper presents a method to interpret the output of a classification (or regression) model. The interpretation is based on two concepts: the variable importance and the value importance of the variable. Unlike most of the state of art interpretation methods, our approach allows the interpretation of the model output for every instance. Understanding the score given by a model for one instance can for example lead to an immediate decision in a customer relational management (CRM) system. Moreover the proposed method does not depend on a particular model and is therefore usable for any model or software used to produce the scores.