Using statistical learning theory for modeling the uncertainty in business and engineering systems: a qualitative introduction

Abstract

Presents a qualitative introduction and justification of the application of statistical learning theory to uncertainty modeling in business and engineering systems. Using simple mathematical tools and metaphorical images, the main variables that govern the uncertainty in a physical system are defined. A general expression of uncertainty models is then obtained. The structure of this expression is the same as that of the uncertainty models that have been developed by rigorously applying the results of statistical learning theory.