Optimal grouping/clustering of items in groups with minimum size
问题 I am looking for an algorithm that solves the following problem: Given: a set of items and their similarity matrix. Goal: group these items in "clusters" of minimum size m Conditions: There are no cluster-like structures in the dataset, as shown in Figure 1 Anyway, the items in a group should be similar to each other. Thus, the global similarity would be high. The motivation is not to identify good clusters but to split a dataset into groups of high similarity and of minimum size.