A modified fuzzy C-means algorithm for feature selection

In this paper we propose a novel method for feature selection based on a modified fuzzy C-means algorithm with supervision (MFCMS). MFCMS adopts an appropriately modified version of the objective function used by the classic fuzzy C-means. We applied MFCMS to some real-world pattern classification b...

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Veröffentlicht in:	2000 19th International Conference of the North American Fuzzy Information Processing Society S. 148 - 152
Hauptverfasser:	Frosini, G., Lazzerini, B., Marcelloni, F.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 2000
Schlagworte:	Benchmark testing Clustering algorithms Fuzzy sets Partitioning algorithms Pattern classification Pattern recognition Prototypes Shape Symmetric matrices
ISBN:	9780780362741, 0780362748
Online-Zugang:	Volltext
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