PLS regression with data partitioning and its connection with fuzzy switching regression models

Abstract

This paper proposes a new approach to switching PLS regression that is a hybrid technique of PLS regression and fuzzy clustering. In the proposed method, the PLS regression part plays a role for estimating lower dimensional latent variables that are useful for prediction of some external criteria while the clustering part is responsible for unsupervised classification of samples considering local data structure.