Rough set based information theoretic approach for clustering uncertain categorical data

MOTIVATION: Many real applications such as businesses and health generate large categorical datasets with uncertainty. A fundamental task is to efficiently discover hidden and non-trivial patterns from such large uncertain categorical datasets. Since the exact value of an attribute is often unknown...

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Detalles Bibliográficos
Autores principales: Uddin, Jamal, Ghazali, Rozaida, H. Abawajy, Jemal, Shah, Habib, Husaini, Noor Aida, Zeb, Asim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106167/
https://www.ncbi.nlm.nih.gov/pubmed/35559954
http://dx.doi.org/10.1371/journal.pone.0265190

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9106167/
https://www.ncbi.nlm.nih.gov/pubmed/35559954
http://dx.doi.org/10.1371/journal.pone.0265190

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