Fuzzy clustering, also called soft clustering or soft k-means, is a form of clustering in which each data point can belong to more than one cluster rather than being assigned to exactly one. Clustering assigns data points to groups so that items in the same cluster are as similar as possible and items in different clusters are as dissimilar as possible, using similarity measures such as distance, connectivity or intensity chosen according to the data or application.
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