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Proposal of new hybrid fuzzy clustering algorithms " Application to breast cancer dataset

COUTINHO, PEDRO HENRIQUE S.; DAS CHAGAS, THIAGO P

2017 • 2017 IEEE Latin American Conference on Computational Intelligence (LACCI) • 4 citações

Resumo

This paper presents new hybrid fuzzy clustering algorithms. The aims of the proposed modifications are to provide robustness for the initial cluster centers using Subtractive clustering and to reduce the number of iterations using the Fuzzy ckMeans center updating strategy. These modifications are applied in the conventional fuzzy clustering algorithms: Fuzzy c-Means, Gustafson-Kessel and Gath-Geva. The proposed methods are applied to Wisconsin Breast Cancer dataset and results compare the proposed algorithms with their conventional forms considering different validity indices and classification accuracy.

Autoria

Autores do grupo (1)

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Pedro Henrique Silva Coutinho

Pesquisador

palavras-chave

Palavras-chave

fuzzy c-means clusteringsubtractive clusteringGustafson-Kessel algorithmcluster center initializationbreast cancer classificationWisconsin Breast Cancer datasetcluster validity indices

Status

Published

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