Fuzzy clustering finding prototypes on classes boundary

Michal Jezewski; Jacek Leski

doi:10.1007/978-3-642-20320-6_19

Fuzzy clustering finding prototypes on classes boundary

Katedra Cybernetyki, Nanotechnologii i Przetwarzania Danych (RAU/RAU10)

Wyniki badań: Wkład do czasopisma › Artykuł › recenzja

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Abstrakt

In the presented paper, new clustering method based on minimization of a criterion function is proposed. Its goal is to find prototypes placed near the classes boundary. The proposed method may be useful in applications to classification algorithms. The clustering performance was examined using the Ripley dataset, and the results seem to be encouraging.

Język oryginału	angielski
Strony (od–do)	177-186
Liczba stron	10
Czasopismo	Advances in Intelligent and Soft Computing
Tom	95
Numer wydania	4
Identyfikatory DOI	https://doi.org/10.1007/978-3-642-20320-6_19
Status publikacji	Opublikowano - 1 maj 2011

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10.1007/978-3-642-20320-6_19

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abstract = "In the presented paper, new clustering method based on minimization of a criterion function is proposed. Its goal is to find prototypes placed near the classes boundary. The proposed method may be useful in applications to classification algorithms. The clustering performance was examined using the Ripley dataset, and the results seem to be encouraging.",

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AB - In the presented paper, new clustering method based on minimization of a criterion function is proposed. Its goal is to find prototypes placed near the classes boundary. The proposed method may be useful in applications to classification algorithms. The clustering performance was examined using the Ripley dataset, and the results seem to be encouraging.

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Fuzzy clustering finding prototypes on classes boundary

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