An Algorithm for Detecting the Principal Allotment among Fuzzy Clusters and Its Application as a Technique of Reduction of Analyzed Features Space Dimensionality

  • Dmitri A. Viattchenin Senior Researcher
Keywords: possibilistic clustering, fuzzy tolerance, allotment among fuzzy clusters, typical point, membership degree, dimensionality reduction

Abstract

This paper describes a modification of a possibilistic clustering method based on the concept of allotment among fuzzy clusters. Basic ideas of the method are considered and the concept of a principal allotment among fuzzy clusters is introduced. The paper provides the description of the plan of the algorithm for detection principal allotment. An analysis of experimental results of the proposed algorithm’s application to the Tamura’s portrait data in comparison with the basic version of the algorithm and with the NERFCM-algorithm is carried out. A methodology of the algorithm’s application to the dimensionality reduction problem is outlined and the application of the methodology is illustrated on the example of Anderson’s Iris data in comparison with the result of principal component analysis. Preliminary conclusions are formulated also.

Author Biography

Dmitri A. Viattchenin, Senior Researcher
Laboratory of Image Recognition and Processing
Published
2009-03-21
Section
Articles