Orthopartitions and soft clustering: Soft mutual information measures for clustering validation
| Autor: | Andrea Campagner, Davide Ciucci |
|---|---|
| Přispěvatelé: | Campagner, A, Ciucci, D |
| Rok vydání: | 2019 |
| Předmět: |
Information Systems and Management
Fuzzy clustering Rough clustering Computer science Uncertainty 02 engineering and technology Mutual information computer.software_genre Orthopartition Soft clustering Management Information Systems Artificial Intelligence 020204 information systems 0202 electrical engineering electronic engineering information engineering Entropy (information theory) 020201 artificial intelligence & image processing Orthopair Data mining Cluster analysis computer Software |
| Zdroj: | Knowledge-Based Systems. 180:51-61 |
| ISSN: | 0950-7051 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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