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- W2361001097 abstract "Clustering is considered as the most important problem of unsupervised learning.A Hierarchical Fuzzy Min-Max Clustering Algorithm(HFMM)is presented based on the original Fuzzy Min- Max Clustering Neural Network(FMMCN)and hierarchical clustering.Compared with the existing methods for clustering,the proposed algorithm dynamically determines the number of clusters to meet the demands of the problem.Moreover it overcomes the shortcomings of FMMCN- order dependent.Experimental results on three databases demonstrate that HFMM has high clustering performance." @default.
- W2361001097 created "2016-06-24" @default.
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- W2361001097 date "2007-01-01" @default.
- W2361001097 modified "2023-09-24" @default.
- W2361001097 title "Hierarchical Fuzzy Min-Max Clustering Algorithm" @default.
- W2361001097 hasPublicationYear "2007" @default.
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