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This paper explores an approach based on the confusion matrix measurement of the feature values with respect to their potential classification outcomes. The approach is able to compute the Discriminative Significances of the features and rank the features unbiasedly with respect to the imbalance ratios of the datasets. Experiment results on real-world and experimental datasets show that the approach made consistent evaluations of the features and identified the most significant ones accordingly on the sparse and binary-valued samples of the class-imbalanced datasets.<\/jats:p>","DOI":"10.1142\/s0218001423500088","type":"journal-article","created":{"date-parts":[[2023,1,26]],"date-time":"2023-01-26T00:58:47Z","timestamp":1674694727000},"source":"Crossref","is-referenced-by-count":2,"title":["Feature Selection Based on the Discriminative Significance for Sparse Binary-Valued and Imbalanced Dataset"],"prefix":"10.1142","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5059-4308","authenticated-orcid":false,"given":"Qiuming","family":"Zhu","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Nebraska at Omaha, Omaha, NE 68182, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2023,3,4]]},"reference":[{"key":"S0218001423500088BIB001","first-page":"304","volume-title":"Encyclopedia of Measurement and Statistics","author":"Abdi H.","year":"2007"},{"issue":"3","key":"S0218001423500088BIB002","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s10844-007-0037-0","volume":"30","author":"Arauzo-Azofra A.","year":"2011","journal-title":"J. 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