Incremental feature selection based on uncertainty measure for dynamic interval-valued data
Incremental feature selection based on uncertainty measure for dynamic interval-valued data
About this item
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Author / Creator
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title
Language
English
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Publication information
Publisher
Berlin/Heidelberg: Springer Berlin Heidelberg
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Scope and Contents
Contents
Feature selection is an important strategy for knowledge reduction in rough set. Interval-valued data, as an extension of single values, can better express uncertain information from the perspective of uncertainty measure. However, for applications in the real world, feature values in interval-valued data vary with time evolving. For dynamic interv...
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Full title
Incremental feature selection based on uncertainty measure for dynamic interval-valued data
Authors, Artists and Contributors
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Record Identifier
TN_cdi_proquest_journals_2942205214
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2942205214
Other Identifiers
ISSN
1868-8071
E-ISSN
1868-808X
DOI
10.1007/s13042-023-01977-5
