The Huber Functions and Their Application to a Classification Problem

Abstract

In the following paper a classification problem with two multivariate normally distributed classes is considered. The problem is solved in a case of an empirical real situation (a motors data) using the Karhunen-Loeve Transform and classifying functions based on estimators for unknown parameters of a multivariate normal distribution. We consider the maximum likelihood estimator and a robust one. The robust estimator bases on the Huber functions. The corresponding classifying functions (classifiers) are compared using the Leave-One-Out method.