Rough set based information theoretic approach for clustering uncertain categorical data
Rough set based information theoretic approach for clustering uncertain categorical data
About this item
Full title
Author / Creator
Publisher
United States: Public Library of Science
Journal title
Language
English
Formats
Publication information
Publisher
United States: Public Library of Science
Subjects
More information
Scope and Contents
Contents
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 in uncertain categorical datasets, conventional clustering ana...
Alternative Titles
Full title
Rough set based information theoretic approach for clustering uncertain categorical data
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_plos_journals_2686248682
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_plos_journals_2686248682
Other Identifiers
ISSN
1932-6203
E-ISSN
1932-6203
DOI
10.1371/journal.pone.0265190
