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Furthermore, the optimal features in the group are selected to flow into the feature space according to the significance of features, and the features with interactions are left. Then, all selected features are re-evaluated by the Lasso model to discard the redundant features. Finally, an online group streaming feature selection algorithm is designed. Experimental results compared with eight representative methods on thirteen datasets show that FNE-OGSFS can achieve better comprehensive performance.<\/jats:p>","DOI":"10.1007\/s40747-022-00763-0","type":"journal-article","created":{"date-parts":[[2022,5,16]],"date-time":"2022-05-16T08:03:31Z","timestamp":1652688211000},"page":"5309-5328","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Online group streaming feature selection using entropy-based uncertainty measures for fuzzy neighborhood rough sets"],"prefix":"10.1007","volume":"8","author":[{"given":"Jiucheng","family":"Xu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9080-5715","authenticated-orcid":false,"given":"Yuanhao","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Kanglin","family":"Qu","sequence":"additional","affiliation":[]},{"given":"Xiangru","family":"Meng","sequence":"additional","affiliation":[]},{"given":"Qinchen","family":"Hou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,5,16]]},"reference":[{"key":"763_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-021-00452-4","author":"C-N Shen","year":"2021","unstructured":"Shen C-N, Zhang K (2021) Two-stage improved Grey Wolf optimization algorithm for feature selection on high-dimensional classification. 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