By Sugato Basu,Ian Davidson,Kiri Wagstaff
The first 5 chapters of this quantity examine advances within the use of instance-level, pairwise constraints for partitional and hierarchical clustering. The publication then explores different varieties of constraints for clustering, together with cluster measurement balancing, minimal cluster size,and cluster-level relational constraints.
It additionally describes adaptations of the conventional clustering less than constraints challenge in addition to approximation algorithms with invaluable functionality promises.
The publication ends by means of employing clustering with constraints to relational facts, privacy-preserving info publishing, and video surveillance facts. It discusses an interactive visible clustering technique, a distance metric studying procedure, existential constraints, and instantly generated constraints.
With contributions from business researchers and major educational specialists who pioneered the sphere, this quantity offers thorough insurance of the functions and boundaries of limited clustering equipment in addition to introduces new forms of constraints and clustering algorithms.
Read Online or Download Constrained Clustering: Advances in Algorithms, Theory, and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) PDF
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