An unsupervised classification scheme for multi-class problems including feature selection based on MTS philosophy Online publication date: Fri, 26-Jun-2009
by Prasun Das, Sandip Mukherjee
International Journal of Industrial and Systems Engineering (IJISE), Vol. 4, No. 6, 2009
Abstract: In this paper, the proposed Unsupervised Mahalanobis Distance Classifier (UNMDC) scheme is a multi-class unsupervised classifier with the basic philosophy of supervised Mahalanobis–Taguchi System (MTS) based monitoring procedure. A comparative study between the MTS and the proposed UNMDC is performed with various simulated experiments for different types of correlation structure and location parameters, published data and real-life data sets of different sizes and dimensions. The advantages of domain knowledge independent thresholds, multi-class separation, identifying process shifts during multivariate process-monitoring and feature selection in case of detection of abnormals are the special merits of this algorithm.
Online publication date: Fri, 26-Jun-2009
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