Analysis of fault tolerance of a combining classifier

Abstract

This paper mainly analyses the fault tolerant capability of a combining classifier that uses a K-voting strategy for integrating binary classifiers. From the point view of fault tolerance, we discuss the influence of the failure of binary classifiers on the final output of the combining classifier, and present a theoretical analysis of combination performance under three fault models. The results provide a theoretical base for fault detection of the combining classifier. © Springer-Verlag 2004.