Hybrid fuzzy clustering using LP norms

Tomasz Przybyła; Janusz Jezewski; Krzysztof Horoba; Dawid Roj

doi:10.1007/978-3-642-20039-7_19

Hybrid fuzzy clustering using L_P norms

Tomasz Przybyła
, Janusz Jezewski
, Krzysztof Horoba
, Dawid Roj

Department of Cybernetics, Nanotechnology and Data Processing (RAU/RAU10)

Institute of Medical Technology and Equipment

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

The fuzzy clustering methods are useful in the data mining applications. This paper describes a new fuzzy clustering method in which each cluster prototype is calculated as a value that minimizes introducted generalized cost function. The generalized cost function utilizes the L _p norm. The fuzzy meridian is a special case of cluster prototype for p = 2 as well as the fuzzy meridian for p = 1. A method for the norm selection is proposed. An example illustrating the performance of the proposed method is given.

Original language	English
Title of host publication	Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings
Publisher	Springer Verlag
Pages	187-196
Number of pages	10
Edition	PART 1
ISBN (Print)	9783642200380
DOIs	https://doi.org/10.1007/978-3-642-20039-7_19
Publication status	Published - 2011
Event	3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011 - Daegu, Korea, Republic of Duration: 20 Apr 2011 → 22 Apr 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	6591 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011
Country/Territory	Korea, Republic of
City	Daegu
Period	20/04/11 → 22/04/11

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-20039-7_19

Cite this

Przybyła, T., Jezewski, J., Horoba, K., & Roj, D. (2011). Hybrid fuzzy clustering using L_P norms. In Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings (PART 1 ed., pp. 187-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6591 LNAI, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-642-20039-7_19

Przybyła, Tomasz ; Jezewski, Janusz ; Horoba, Krzysztof et al. / Hybrid fuzzy clustering using L_P norms. Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings. PART 1. ed. Springer Verlag, 2011. pp. 187-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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abstract = "The fuzzy clustering methods are useful in the data mining applications. This paper describes a new fuzzy clustering method in which each cluster prototype is calculated as a value that minimizes introducted generalized cost function. The generalized cost function utilizes the L p norm. The fuzzy meridian is a special case of cluster prototype for p = 2 as well as the fuzzy meridian for p = 1. A method for the norm selection is proposed. An example illustrating the performance of the proposed method is given.",

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Przybyła, T, Jezewski, J, Horoba, K & Roj, D 2011, Hybrid fuzzy clustering using L_P norms. in Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 6591 LNAI, Springer Verlag, pp. 187-196, 3rd International Conference on Intelligent Information and Database Systems, ACIIDS 2011, Daegu, Korea, Republic of, 20/04/11. https://doi.org/10.1007/978-3-642-20039-7_19

Hybrid fuzzy clustering using L_P norms. / Przybyła, Tomasz; Jezewski, Janusz; Horoba, Krzysztof et al.
Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings. PART 1. ed. Springer Verlag, 2011. p. 187-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6591 LNAI, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - The fuzzy clustering methods are useful in the data mining applications. This paper describes a new fuzzy clustering method in which each cluster prototype is calculated as a value that minimizes introducted generalized cost function. The generalized cost function utilizes the L p norm. The fuzzy meridian is a special case of cluster prototype for p = 2 as well as the fuzzy meridian for p = 1. A method for the norm selection is proposed. An example illustrating the performance of the proposed method is given.

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Przybyła T, Jezewski J, Horoba K, Roj D. Hybrid fuzzy clustering using L_P norms. In Intelligent Information and Database Systems - Third International Conference, ACIIDS 2011, Proceedings. PART 1 ed. Springer Verlag. 2011. p. 187-196. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-642-20039-7_19