Robust centroids using fuzzy clustering with feature partitions
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.
fuzzy c-means functional magnetic resonance imaging noise