Abstract
General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.
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Bavaud, F. Aggregation invariance in general clustering approaches. Adv Data Anal Classif 3, 205–225 (2009). https://doi.org/10.1007/s11634-009-0052-9
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DOI: https://doi.org/10.1007/s11634-009-0052-9
Keywords
- Aggregation invariance
- c-Means clustering
- EM algorithm
- Fuzzy clustering
- Model-based clustering
- Mutual information