Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence

H Zhao, P Wang, Q Hu - Information Sciences, 2016 - Elsevier
Neighborhood rough set model is considered as one of the effective granular computing
models in dealing with numerical data. This model is now widely discussed in feature …
被引用次数：79 相关文章

Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence

H Zhao, P Wang, Q Hu - Information Sciences, 2016 - infona.pl
Neighborhood rough set model is considered as one of the effective granular computing
models in dealing with numerical data. This model is now widely discussed in feature …
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[PDF][PDF] Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence

H Zhao, P Wang, Q Hu - Information Sciences, 2016 - drive.google.com
abstract Neighborhood rough set model is considered as one of the effective granular
computing models in dealing with numerical data. This model is now widely discussed in …

Cost-sensitive feature selection based on adaptive neighborhood granularity with multi-level confidence

H Zhao, P Wang, Q Hu - Information Sciences—Informatics and …, 2016 - dl.acm.org
Neighborhood rough set model is considered as one of the effective granular computing
models in dealing with numerical data. This model is now widely discussed in feature …