Robust centroids using fuzzy clustering with feature partitions

Authors:
Mark D. Alexiuk;Nicolino J. Pizzi
Affiliations:
Institute for Biodiagnostics, National Research Council, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6;Institute for Biodiagnostics, National Research Council, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6
Venue:
Pattern Recognition Letters
Year:
2005

Citing 6
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Abstract

Fuzzy c-means with feature partitions uses a generalized metric on feature subsets to increase centroid robustness. Each feature partition may use a unique metric and is weighted for relevance. This method is demonstrated on synthetic and real datasets.