{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T05:57:05Z","timestamp":1777874225862,"version":"3.51.4"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009329","name":"Scientific Research and Technology Development Program of Guangxi","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100009329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.neucom.2026.133609","type":"journal-article","created":{"date-parts":[[2026,4,12]],"date-time":"2026-04-12T16:31:15Z","timestamp":1776011475000},"page":"133609","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["UAMOD: Unsupervised feature selection algorithm using adaptive multi-neighborhood fuzzy entropy for outlier detection"],"prefix":"10.1016","volume":"685","author":[{"given":"Nana","family":"Luo","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4695-8746","authenticated-orcid":false,"given":"Chao","family":"Jing","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"6","key":"10.1016\/j.neucom.2026.133609_bib0005","doi-asserted-by":"crossref","DOI":"10.1145\/3136625","article-title":"Feature selection: a data perspective","volume":"50","author":"Li","year":"2017","journal-title":"ACM Comput. Surv."},{"issue":"5","key":"10.1016\/j.neucom.2026.133609_bib0010","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TCBB.2015.2478454","article-title":"Supervised, unsupervised, and semi-supervised feature selection: a review on gene selection","volume":"13","author":"Ang","year":"2016","journal-title":"IEEE\/ACM Trans. Comput. Biol. Bioinform."},{"key":"10.1016\/j.neucom.2026.133609_bib0015","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.patcog.2016.11.003","article-title":"A survey on semi-supervised feature selection methods","volume":"64","author":"Sheikhpour","year":"2017","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133609_bib0020","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1007\/s10462-019-09682-y","article-title":"A review of unsupervised feature selection methods","volume":"53","author":"Solorio-Fern\u00e1ndez","year":"2020","journal-title":"Artif. Intell. Rev."},{"issue":"11","key":"10.1016\/j.neucom.2026.133609_bib0025","doi-asserted-by":"crossref","first-page":"5257","DOI":"10.1109\/TIP.2017.2733200","article-title":"Lle score: a new filter-based unsupervised feature selection method based on nonlinear manifold embedding and its application to image recognition","volume":"26","author":"Yao","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2026.133609_bib0030","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.ins.2021.02.061","article-title":"A novel wrapper-based feature subset selection method using modified binary differential evolution algorithm","volume":"565","author":"Tarkhaneh","year":"2021","journal-title":"Inf. Sci."},{"key":"10.1016\/j.neucom.2026.133609_bib0035","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.101948","article-title":"A survey on multi-label feature selection from perspectives of label fusion","volume":"100","author":"Qian","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.neucom.2026.133609_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107663","article-title":"Pairwise dependence-based unsupervised feature selection","volume":"111","author":"Lim","year":"2021","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.neucom.2026.133609_bib0045","doi-asserted-by":"crossref","first-page":"305","DOI":"10.3934\/mbe.2021016","article-title":"Feature selection based on fuzzy joint mutual information maximization","volume":"18","author":"Salem","year":"2021","journal-title":"Math. Biosci. Eng."},{"key":"10.1016\/j.neucom.2026.133609_bib0050","series-title":"Proceedings of the 18th International Conference on Neural Information Processing Systems (NIPS 2005)","first-page":"507","article-title":"Laplacian score for feature selection","author":"He","year":"2005"},{"issue":"3","key":"10.1016\/j.neucom.2026.133609_bib0055","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1109\/34.990133","article-title":"Unsupervised feature selection using feature similarity","volume":"24","author":"Mitra","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133609_bib0060","series-title":"Spectral Feature Selection for Supervised and Unsupervised Learning","first-page":"1151","author":"Zhao","year":"2007"},{"key":"10.1016\/j.neucom.2026.133609_bib0065","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.engappai.2014.03.007","article-title":"An unsupervised feature selection algorithm based on ant colony optimization","volume":"32","author":"Tabakhi","year":"2014","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2","key":"10.1016\/j.neucom.2026.133609_bib0070","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1016\/j.patcog.2014.08.006","article-title":"Unsupervised feature selection by regularized self-representation","volume":"48","author":"Zhu","year":"2015","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133609_bib0075","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.patcog.2017.07.020","article-title":"A new unsupervised spectral feature selection method for mixed data: a filter approach","volume":"72","author":"Solorio-Fern\u00e1ndez","year":"2017","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133609_bib0080","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2021.114563","article-title":"Two-stage approach to feature set optimization for unsupervised dataset with heterogeneous attributes","volume":"172","author":"Chaudhuri","year":"2021","journal-title":"Expert Syst. Appl."},{"issue":"9","key":"10.1016\/j.neucom.2026.133609_bib0085","doi-asserted-by":"crossref","first-page":"3395","DOI":"10.1109\/TFUZZ.2021.3114734","article-title":"A novel unsupervised approach to heterogeneous feature selection based on fuzzy mutual information","volume":"30","author":"Yuan","year":"2022","journal-title":"IEEE Trans. Fuzzy Syst."},{"key":"10.1016\/j.neucom.2026.133609_bib0090","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.108651","article-title":"Exploring interactive attribute reduction via fuzzy complementary entropy for unlabeled mixed data","volume":"127","author":"Yuan","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133609_bib0095","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112572","article-title":"Fuzzy multi-neighborhood entropy-based interactive feature selection for unsupervised outlier detection","volume":"169","author":"Yang","year":"2025","journal-title":"Appl. Soft Comput."},{"issue":"12","key":"10.1016\/j.neucom.2026.133609_bib0100","doi-asserted-by":"crossref","first-page":"4396","DOI":"10.1109\/TPAMI.2020.3002843","article-title":"Infinite feature selection: a graph-based feature filtering approach","volume":"43","author":"Roffo","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133609_bib0105","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113745","article-title":"A systematic evaluation of filter unsupervised feature selection methods","volume":"162","author":"Solorio-Fern\u00e1ndez","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.133609_bib0110","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.eswa.2016.01.021","article-title":"Unsupervised probabilistic feature selection using ant colony optimization","volume":"53","author":"Dadaneh","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.133609_bib0115","article-title":"Multi-cluster nonlinear unsupervised feature selection via joint manifold learning and generalized lasso","volume":"255","author":"Wang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.133609_bib0120","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1016\/j.neucom.2015.05.022","article-title":"Gene selection for microarray data classification using a novel ant colony optimization","volume":"168","author":"Tabakhi","year":"2015","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.neucom.2026.133609_bib0125","doi-asserted-by":"crossref","first-page":"151","DOI":"10.21629\/JSEE.2017.01.17","article-title":"Unsupervised feature selection based on markov blanket and particle swarm optimization","volume":"28","author":"Wang","year":"2017","journal-title":"J. Syst. Eng. Electron."},{"key":"10.1016\/j.neucom.2026.133609_bib0130","first-page":"134","article-title":"Unsupervised gene selection using particle swarm optimization and k-means","volume":"348","author":"Deepthi","year":"2015","journal-title":"Adv. Intell. Syst. Comput."},{"key":"10.1016\/j.neucom.2026.133609_bib0135","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2019.07.027","article-title":"Unsupervised feature selection with multi-subspace randomization and collaboration","volume":"182","author":"Huang","year":"2019","journal-title":"Knowl.-based Syst."},{"issue":"6","key":"10.1016\/j.neucom.2026.133609_bib0140","first-page":"1619","article-title":"A study on feature selection method based on hybrid evolutionary algorithm","volume":"51","author":"Gao","year":"2023","journal-title":"Journal of Electronics (China)"},{"key":"10.1016\/j.neucom.2026.133609_bib0145","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2023.110183","article-title":"Unsupervised feature selection by learning exponential weights","volume":"148","author":"Wang","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.neucom.2026.133609_bib0150","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"5016","article-title":"Unsupervised simultaneous orthogonal basis clustering feature selection","author":"Han","year":"2015"},{"issue":"11","key":"10.1016\/j.neucom.2026.133609_bib0155","doi-asserted-by":"crossref","first-page":"6881","DOI":"10.1109\/TNNLS.2021.3083763","article-title":"Unsupervised feature selection via orthogonal basis clustering and local structure preserving","volume":"33","author":"Lin","year":"2022","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.133609_bib0160","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.neunet.2023.06.018","article-title":"Unsupervised feature selection based on variance\u2013covariance subspace distance","volume":"166","author":"Karami","year":"2023","journal-title":"Neural Netw."},{"key":"10.1016\/j.neucom.2026.133609_bib0165","series-title":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence - Volume Volume Two","first-page":"1589","article-title":"L2, 1-norm regularized discriminative feature selection for unsupervised learning","author":"Yang","year":"2011"},{"key":"10.1016\/j.neucom.2026.133609_bib0170","doi-asserted-by":"crossref","first-page":"93511","DOI":"10.1109\/ACCESS.2023.3274469","article-title":"A hybrid feature selection method using an improved binary butterfly optimization algorithm and adaptive \u03b2-hill climbing","volume":"11","author":"Tiwari","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.neucom.2026.133609_bib0175","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111483","article-title":"Unsupervised feature selection via maximum relevance and minimum global redundancy","volume":"164","author":"Zuo","year":"2025","journal-title":"Pattern Recognit."},{"issue":"5","key":"10.1016\/j.neucom.2026.133609_bib0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104173","article-title":"I2qd: unsupervised feature selection via information quality, quantity, and difference degree","volume":"62","author":"Zhang","year":"2025","journal-title":"Information Processing and Management"},{"issue":"15","key":"10.1016\/j.neucom.2026.133609_bib0185","article-title":"Feature subset selection for multi-scale neighborhood decision information system via mutual information","volume":"57","author":"Zhang","year":"2024","journal-title":"Artif. Intell. Rev."},{"issue":"2","key":"10.1016\/j.neucom.2026.133609_bib0190","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1109\/TKDE.2020.2983396","article-title":"Unsupervised discriminative projection for feature selection","volume":"34","author":"Wang","year":"2022","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.neucom.2026.133609_bib0195","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.116621","article-title":"A hybrid feature selection approach based on information theory and dynamic butterfly optimization algorithm for data classification","volume":"196","author":"Tiwari","year":"2022","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.neucom.2026.133609_bib0200","series-title":"Proceedings of the 25th Conference on Proceedings of the 25th IASTED International Multi-Conference: Artificial Intelligence and Applications, AIAP\u201907","first-page":"390","article-title":"A stability index for feature selection","author":"Kuncheva","year":"2007"},{"issue":"3","key":"10.1016\/j.neucom.2026.133609_bib0205","doi-asserted-by":"crossref","first-page":"1978","DOI":"10.1109\/TIT.2023.3331010","article-title":"Matrices with Gaussian noise: optimal estimates for singular subspace perturbation","volume":"70","author":"O\u2019Rourke","year":"2024","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"8","key":"10.1016\/j.neucom.2026.133609_bib0210","doi-asserted-by":"crossref","first-page":"1226","DOI":"10.1109\/TPAMI.2005.159","article-title":"Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy","volume":"27","author":"Peng","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.133609_bib0215","doi-asserted-by":"crossref","DOI":"10.1177\/17483026221078111","article-title":"Outlier detection algorithm based on k-nearest neighbors-local outlier factor","volume":"16","author":"Xu","year":"2022","journal-title":"J. Algorithms Comput. Technol."},{"key":"10.1016\/j.neucom.2026.133609_bib0220","series-title":"Proceedings of KI-2012: Poster and Demo Track","first-page":"59","article-title":"Histogram-based outlier score (HBOS): a fast unsupervised anomaly detection algorithm","author":"Goldstein","year":"2012"},{"issue":"12","key":"10.1016\/j.neucom.2026.133609_bib0225","doi-asserted-by":"crossref","first-page":"12181","DOI":"10.1109\/TKDE.2022.3159580","article-title":"Ecod: unsupervised outlier detection using empirical cumulative distribution functions","volume":"35","author":"Li","year":"2023","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"8","key":"10.1016\/j.neucom.2026.133609_bib0230","doi-asserted-by":"crossref","first-page":"8399","DOI":"10.1109\/TCYB.2021.3058780","article-title":"Outlier detection based on fuzzy rough granules in mixed attribute data","volume":"52","author":"Yuan","year":"2022","journal-title":"IEEE Trans. Cybern."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226010064?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226010064?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T19:21:03Z","timestamp":1777576863000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226010064"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":46,"alternative-id":["S0925231226010064"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133609","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"UAMOD: Unsupervised feature selection algorithm using adaptive multi-neighborhood fuzzy entropy for outlier detection","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.133609","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"133609"}}