In this work, we introduce the notion of orthopartition as a generalized partition with uncertainty. Several entropy-based measures are then developed to measure this intrinsic uncertainty, which are in turn applied to soft clustering. An application is explored: the use of the new Soft Mutual Information Measures to evaluate the performances of soft clustering algorithms. The new measures and methods are then tested on standard datasets, showing their applicability to rough clustering

Campagner, A., Ciucci, D. (2019). Orthopartitions and soft clustering: Soft mutual information measures for clustering validation. KNOWLEDGE-BASED SYSTEMS, 180, 51-61 [10.1016/j.knosys.2019.05.018].

Orthopartitions and soft clustering: Soft mutual information measures for clustering validation

Campagner, A;Ciucci, D.
2019

Abstract

In this work, we introduce the notion of orthopartition as a generalized partition with uncertainty. Several entropy-based measures are then developed to measure this intrinsic uncertainty, which are in turn applied to soft clustering. An application is explored: the use of the new Soft Mutual Information Measures to evaluate the performances of soft clustering algorithms. The new measures and methods are then tested on standard datasets, showing their applicability to rough clustering
Articolo in rivista - Articolo scientifico
Mutual information; Orthopair; Orthopartition; Rough clustering; Soft clustering; Uncertainty
English
2019
180
51
61
reserved
Campagner, A., Ciucci, D. (2019). Orthopartitions and soft clustering: Soft mutual information measures for clustering validation. KNOWLEDGE-BASED SYSTEMS, 180, 51-61 [10.1016/j.knosys.2019.05.018].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/240580
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