Pivotal seeding for K-means based on clustering ensembles
Autor: | Leonardo Egidi, Roberta Pappadà, Francesco Pauli, Nicola Torelli |
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Přispěvatelé: | Società Italiana di Statistica, Giuseppe Arbia, Stefano Peluso, Alessia Pini, Giulia Rivellini, Egidi, Leonardo, Pappada', Roberta, Pauli, Francesco, Torelli, Nicola |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: | |
Popis: | Despite its large use, one major limitation of K-means algorithm is the impact of the initial seeding on the final partition. We propose a modified version, using the information contained in a co-association matrix obtained from clustering ensembles; such matrix is given as input for a set of pivotal methods, implemented in the pivmet R package, used to perform a pivot-based initialization step. Preliminary results concerning the comparison with the classical approach and other clustering methods are discussed. |
Databáze: | OpenAIRE |
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