Principal Component Analysis based on Fuzzy Objective Functions

Abstract

In this paper, we propose a robust principal component analysis algorithm based on a fuzzy objective function. By defining a fuzzy objective function for considering the outliers in principal component analysis, we derive an on-line robust algorithm that can extract the appropriate principal components from the spoiled data set. An artificially generated data set is used to evaluate the performance of the proposed algorithm.