Skoči na glavni sadržaj

Izvorni znanstveni članak

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 ; United Institute of Informatics Problems, National Academy of Sciences of Belarus, Belarus


Puni tekst: engleski pdf 287 Kb

str. 205-217

preuzimanja: 410

citiraj


Sažetak

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.

Ključne riječi

possibilistic clustering; fuzzy tolerance; allotment among fuzzy clusters; typical point; membership degree; dimensionality reduction

Hrčak ID:

38743

URI

https://hrcak.srce.hr/38743

Datum izdavanja:

6.7.2009.

Posjeta: 751 *