Classification and Regression Trees (CART)

Abstract

ABSTRACT In many application areas of Statistics, individuals (observational units) are portrayed by multidimensional quantitative and / or qualitative information; on the other hand, we have an individual response (output) sometimes quantitative, in other qualitative. Often the most interesting response values are associated to individuals that, in some sense, are special; to identify profiles that describe such individuals is of central interest but the quest to find them is not merely linear but rather is comparable to a tree structure given by successive divisions. The underlying models are not as simple as a multiple linear regression model. This methodology is intensive in the use of computational resources demanding software ad-hoc. In this article we describe the methodology CART illustrated with three applications related to real chilean health problems of children, adolescent and workers. Descriptors: