The feasible solution algorithm for fuzzy least trimmed squares clustering

Amit Banerjee; Rajesh N. Davé

doi:10.1109/nafips.2004.1336281

The feasible solution algorithm for fuzzy least trimmed squares clustering

Amit Banerjee, Rajesh N. Davé

Research output: Contribution to conference › Paper › peer-review

5 Scopus citations

Abstract

The issue of sensitivity to noise and outliers of LS minimization based clustering techniques, is addressed In this paper. A novel and robust clustering scheme based on the feasible solution algorithm that implements the Least Trimmed Squares (LTS) estimator, is developed, implemented and the results presented. The LTS estimator is known to be resistant to noise and has a high breakdown point. The feasible solution algorithm approach also guarantees convergence of the solution set to a global optima. Our experiments show the practicability of the proposed scheme in terms of computational requirements and in the attractiveness of its simplistic framework.

Original language	English (US)
Pages	222-227
Number of pages	6
DOIs	https://doi.org/10.1109/nafips.2004.1336281
State	Published - 2004
Event	NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies - Banff, Alta, Canada Duration: Jun 27 2004 → Jun 30 2004

Other

Other	NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies
Country/Territory	Canada
City	Banff, Alta
Period	6/27/04 → 6/30/04

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

Keywords

Fuzzy clustering
High breakdown estimators
Least trimmed squares
Outliers
Robust clustering

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10.1109/nafips.2004.1336281

Cite this

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title = "The feasible solution algorithm for fuzzy least trimmed squares clustering",

abstract = "The issue of sensitivity to noise and outliers of LS minimization based clustering techniques, is addressed In this paper. A novel and robust clustering scheme based on the feasible solution algorithm that implements the Least Trimmed Squares (LTS) estimator, is developed, implemented and the results presented. The LTS estimator is known to be resistant to noise and has a high breakdown point. The feasible solution algorithm approach also guarantees convergence of the solution set to a global optima. Our experiments show the practicability of the proposed scheme in terms of computational requirements and in the attractiveness of its simplistic framework.",

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The feasible solution algorithm for fuzzy least trimmed squares clustering. / Banerjee, Amit; Davé, Rajesh N.
2004. 222-227 Paper presented at NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies, Banff, Alta, Canada.

Research output: Contribution to conference › Paper › peer-review

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AU - Davé, Rajesh N.

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AB - The issue of sensitivity to noise and outliers of LS minimization based clustering techniques, is addressed In this paper. A novel and robust clustering scheme based on the feasible solution algorithm that implements the Least Trimmed Squares (LTS) estimator, is developed, implemented and the results presented. The LTS estimator is known to be resistant to noise and has a high breakdown point. The feasible solution algorithm approach also guarantees convergence of the solution set to a global optima. Our experiments show the practicability of the proposed scheme in terms of computational requirements and in the attractiveness of its simplistic framework.

KW - Fuzzy clustering

KW - High breakdown estimators

KW - Least trimmed squares

KW - Outliers

KW - Robust clustering

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T2 - NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies

Y2 - 27 June 2004 through 30 June 2004

ER -

The feasible solution algorithm for fuzzy least trimmed squares clustering

Abstract

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All Science Journal Classification (ASJC) codes

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