Multilinear objective function-based clustering
Published in arXiv (Cornell University) • Sep 26, 2015
NobleIDNI6P27W63R43S00
Authors:
Giovanni Rossi
Abstract
The input of most clustering algorithms is a symmetric matrix quantifying similarity within data pairs. Such a matrix is here turned into a quadratic set function measuring cluster score or similarity within data subsets larger than pairs. In general, any set function reasonably assigning a cluster ...
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