M-estimators and robust fuzzy clustering

Author

Davé, Rajesh N. ; Krishnapuram, Raghu

Author_Institution

Dept. of Mech. Eng., New Jersey Inst. of Technol., Newark, NJ, USA

fYear

1996

fDate

19-22 Jun 1996

Firstpage

400

Lastpage

404

Abstract

We compare several recent robust fuzzy clustering methods and show their equivalence in terms of their connection to techniques in robust statistics. In particular, we establish a connection between fuzzy set theory (as used in robust fuzzy clustering methods) and robust statistics, and point out the similarities between robust clustering methods and statistical methods such as the the M-estimator. We also give qualitative and quantitative equivalence of the robust fuzzy clustering techniques with M-estimator

Keywords

estimation theory; fuzzy set theory; pattern recognition; statistical analysis; M-estimators; fuzzy set theory; quantitative equivalence; robust fuzzy clustering; robust statistics; statistical methods; Clustering algorithms; Clustering methods; Fuzzy set theory; Fuzzy sets; Mechanical engineering; Noise robustness; Phase change materials; Prototypes; Statistical analysis; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 1996. NAFIPS., 1996 Biennial Conference of the North American

Conference_Location

Berkeley, CA

Print_ISBN

0-7803-3225-3

Type

conf

DOI

10.1109/NAFIPS.1996.534767

Filename

534767

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2592973