Hard clustering describes a family of algorithms where each sample in a dataset is assigned to exactly one cluster, as in the k-means algorithm that we discussed in the previous subsection. In contrast, algorithms for soft clustering (sometimes also called fuzzy clustering) assign a sample to one or more clusters. A popular example of soft clustering is the fuzzy C-means (FCM) algorithm (also called soft k-means or fuzzy k-means).
