{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T04:23:37Z","timestamp":1769747017916,"version":"3.49.0"},"reference-count":52,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71702066"],"award-info":[{"award-number":["71702066"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71802192"],"award-info":[{"award-number":["71802192"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61703319"],"award-info":[{"award-number":["61703319"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71772077"],"award-info":[{"award-number":["71772077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M612856"],"award-info":[{"award-number":["2017M612856"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002338","name":"Ministry of Education of China","doi-asserted-by":"publisher","award":["18YJC630137"],"award-info":[{"award-number":["18YJC630137"]}],"id":[{"id":"10.13039\/501100002338","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&D Program of China","award":["2017YFB0102500"],"award-info":[{"award-number":["2017YFB0102500"]}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Decision Support Systems"],"published-print":{"date-parts":[[2019,7]]},"DOI":"10.1016\/j.dss.2019.05.004","type":"journal-article","created":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T11:11:26Z","timestamp":1559301086000},"page":"113064","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":12,"special_numbering":"C","title":["Feature assessment and ranking for classification with nonlinear sparse representation and approximate dependence analysis"],"prefix":"10.1016","volume":"122","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6269-1239","authenticated-orcid":false,"given":"Yishi","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zhijun","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7400-9954","authenticated-orcid":false,"given":"Jennifer","family":"Shang","sequence":"additional","affiliation":[]},{"given":"Haiying","family":"Wei","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.dss.2019.05.004_bb0005","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.dss.2018.01.005","article-title":"Automatic feature weighting for improving financial Decision Support Systems","volume":"107","author":"Serrano-Silva","year":"2018","journal-title":"Decision Support Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0010","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.dss.2017.10.007","article-title":"Integrated framework for profit-based feature selection and SVM classification in credit scoring","volume":"104","author":"Maldonado","year":"2017","journal-title":"Decision Support Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0015","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.cviu.2015.07.007","article-title":"Adaptive facial point detection and emotion recognition for a humanoid robot","volume":"140","author":"Zhang","year":"2015","journal-title":"Computer Vision and Image Understanding"},{"key":"10.1016\/j.dss.2019.05.004_bb0020","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.asoc.2015.05.006","article-title":"Intelligent facial emotion recognition using a layered encoding cascade optimization model","volume":"34","author":"Neoh","year":"2015","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.dss.2019.05.004_bb0025","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.knosys.2016.08.018","article-title":"Intelligent facial emotion recognition using moth-firefly optimization","volume":"111","author":"Zhang","year":"2016","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0030","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.knosys.2018.05.042","article-title":"Intelligent skin cancer detection using enhanced particle swarm optimization","volume":"158","author":"Tan","year":"2018","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0035","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.asoc.2017.03.024","article-title":"Intelligent leukaemia diagnosis with bare-bones PSO based feature optimization","volume":"56","author":"Srisukkham","year":"2017","journal-title":"Applied Soft Computing"},{"key":"10.1016\/j.dss.2019.05.004_bb0040","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.dss.2017.12.001","article-title":"Feature selection using firefly optimization for classification and regression models","volume":"106","author":"Zhang","year":"2018","journal-title":"Decision Support Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0045","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","article-title":"Wrappers for feature subset selection","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artificial Intelligence"},{"key":"10.1016\/j.dss.2019.05.004_bb0050","first-page":"27","article-title":"Conditional likelihood maximisation: a unifying framework for information theoretic feature selection","volume":"13","author":"Brown","year":"2012","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0055","first-page":"1813","article-title":"A unified algorithm for mixed \u21132,p-minimizations and its application in feature selection","volume":"23","author":"Wang","year":"2010","journal-title":"Advances in Neural Information Processing Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0060","first-page":"1491","article-title":"Quadratic programming feature selection","volume":"11","author":"Rodriguez-Lujan","year":"2010","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0065","first-page":"1157","article-title":"An introduction to variable and features election","volume":"3","author":"Guyon","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0070","series-title":"Proceedings of the Workshop on Speech and Natural Language","first-page":"212","article-title":"Feature selection and feature extraction for text categorization","author":"Lewis","year":"1992"},{"key":"10.1016\/j.dss.2019.05.004_bb0075","first-page":"1205","article-title":"Efficient feature selection via analysis of relevance and redundancy","volume":"5","author":"Yu","year":"2004","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0080","first-page":"91","article-title":"On the use of variable complementarity for feature selection in cancer classification","volume":"3907","author":"Meyer","year":"2006","journal-title":"Evolutionary Computation and Machine Learning in Bioinformatics"},{"issue":"8","key":"10.1016\/j.dss.2019.05.004_bb0085","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 Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.dss.2019.05.004_bb0090","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.knosys.2018.05.002","article-title":"A scattering and repulsive swarm intelligence algorithm for solving global optimization problems","volume":"156","author":"Pandit","year":"2018","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0095","first-page":"1531","article-title":"Fast binary feature selection with conditional mutual information","volume":"5","author":"Fleuret","year":"2004","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0100","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.neucom.2015.03.081","article-title":"Feature selection for classification with class-separability strategy and data envelopment analysis","volume":"166","author":"Zhang","year":"2015","journal-title":"Neurocomputing"},{"issue":"5","key":"10.1016\/j.dss.2019.05.004_bb0105","doi-asserted-by":"crossref","first-page":"2832","DOI":"10.1137\/090761471","article-title":"Lower bound theory of nonzero entries in solutions of \u21132\u202f\u2212\u202f\u2113p minimization","volume":"32","author":"Chen","year":"2010","journal-title":"SIAM Journal on Scientific Computing"},{"issue":"2","key":"10.1016\/j.dss.2019.05.004_bb0110","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1214\/009053604000000067","article-title":"Least angle regression","volume":"32","author":"Efron","year":"2004","journal-title":"Annals of Statistics"},{"issue":"10","key":"10.1016\/j.dss.2019.05.004_bb0115","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1109\/TPAMI.2015.2505311","article-title":"Joint feature selection and subspace learning for cross-modal retrieval","volume":"38","author":"Wang","year":"2016","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"1","key":"10.1016\/j.dss.2019.05.004_bb0120","first-page":"8279","article-title":"An error bound for \u21131-norm support vector machine coefficients in ultra-high dimension","volume":"17","author":"Peng","year":"2016","journal-title":"The Journal of Machine Learning Research"},{"issue":"1","key":"10.1016\/j.dss.2019.05.004_bb0125","doi-asserted-by":"crossref","first-page":"298","DOI":"10.1109\/TCYB.2015.2401733","article-title":"Pairwise constraint-guided sparse learning for feature selection","volume":"46","author":"Liu","year":"2016","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"4","key":"10.1016\/j.dss.2019.05.004_bb0130","doi-asserted-by":"crossref","first-page":"796","DOI":"10.1109\/TNNLS.2015.2424721","article-title":"Effective Discriminative Feature Selection With Nontrivial Solution","volume":"27","author":"Tao","year":"2016","journal-title":"IEEE Transactions on Neural Networks & Learning Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0135","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.knosys.2015.07.004","article-title":"Feature selection with redundancy-complementariness dispersion","volume":"89","author":"Chen","year":"2015","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0140","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.knosys.2014.03.022","article-title":"Feature selection using data envelopment analysis","volume":"64","author":"Zhang","year":"2014","journal-title":"Knowledge-Based Systems"},{"issue":"3","key":"10.1016\/j.dss.2019.05.004_bb0145","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1109\/JSTSP.2008.923858","article-title":"Information-theoretic feature selection in microarray data using variable complementarity","volume":"2","author":"Meyer","year":"2008","journal-title":"IEEE Journal of Selected Topics in Signal Processing"},{"key":"10.1016\/j.dss.2019.05.004_bb0150","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.eswa.2017.10.001","article-title":"Classifier ensemble reduction using a modified firefly algorithm: an empirical evaluation","volume":"93","author":"Zhang","year":"2018","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"10.1016\/j.dss.2019.05.004_bb0155","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TKDE.2011.181","article-title":"A fast clustering-based feature subset selection algorithm for high-dimensional data","volume":"25","author":"Song","year":"2013","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.dss.2019.05.004_bb0160","series-title":"Proceedings of International ICSC Symposium on Advances in Intelligent Data Analysis","first-page":"22","article-title":"Feature selection based on joint mutual information","author":"Yang","year":"1999"},{"key":"10.1016\/j.dss.2019.05.004_bb0165","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1016\/j.patcog.2016.08.011","article-title":"An efficient semi-supervised representatives feature selection algorithm based on information theory","volume":"61","author":"Liang","year":"2017","journal-title":"Pattern Recognition"},{"issue":"4","key":"10.1016\/j.dss.2019.05.004_bb0170","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1109\/TKDE.2017.2650906","article-title":"Feature selection by maximizing independent classification information","volume":"29","author":"Wang","year":"2017","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.dss.2019.05.004_bb0175","first-page":"1813","article-title":"Efficient and robust feature selection via joint \u21132,1-norms minimization","volume":"23","author":"Nie","year":"2010","journal-title":"Advances in Neural Information Processing Systems"},{"issue":"1","key":"10.1016\/j.dss.2019.05.004_bb0180","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.ejor.2014.11.031","article-title":"DC approximation approaches for sparse optimization","volume":"244","author":"Thi","year":"2015","journal-title":"European Journal of Operational Research"},{"key":"10.1016\/j.dss.2019.05.004_bb0185","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1080\/01621459.2013.877275","article-title":"Sequential lasso cum EBIC for feature selection with ultra-high dimensional feature space","volume":"109","author":"Luo","year":"2014","journal-title":"Journal of the American Statistical Association"},{"issue":"3","key":"10.1016\/j.dss.2019.05.004_bb0190","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.acha.2008.09.001","article-title":"Sparsest solutions of underdetermined linear systems via \u2113q-minimization for 0 < q < 1","volume":"26","author":"Foucart","year":"2009","journal-title":"Applied and Computational Harmonic Analysis"},{"issue":"7","key":"10.1016\/j.dss.2019.05.004_bb0195","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1109\/TNNLS.2012.2197412","article-title":"L1\/2 regularization: a thresholding representation theory and a fast solver","volume":"23","author":"Xu","year":"2012","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"6","key":"10.1016\/j.dss.2019.05.004_bb0200","first-page":"1159","article-title":"L1\/2 regularization","volume":"53","author":"Xu","year":"2010","journal-title":"Science China"},{"issue":"1-2","key":"10.1016\/j.dss.2019.05.004_bb0205","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1007\/s10107-012-0613-0","article-title":"Complexity of unconstrained \u21132\u202f\u2212\u202f\u2113p minimization","volume":"143","author":"Chen","year":"2014","journal-title":"Mathematical Programming"},{"key":"10.1016\/j.dss.2019.05.004_bb0210","series-title":"Proceedings of the 27th International Conference on International Conference on Machine Learning, ICML\u201910","first-page":"751","article-title":"From Transformation-based Dimensionality Reduction to Feature Selection","author":"Masaeli","year":"2010"},{"key":"10.1016\/j.dss.2019.05.004_bb0215","doi-asserted-by":"crossref","first-page":"4203","DOI":"10.1109\/TIT.2005.858979","article-title":"Decoding by linear programming","volume":"51","author":"Candes","year":"2005","journal-title":"IEEE Transactions on Information Theory"},{"issue":"7","key":"10.1016\/j.dss.2019.05.004_bb0220","doi-asserted-by":"crossref","first-page":"4680","DOI":"10.1109\/TIT.2011.2146090","article-title":"Orthogonal matching pursuit for sparse signal recovery with noise","volume":"57","author":"Cai","year":"2011","journal-title":"IEEE Transactions on Information Theory"},{"issue":"4","key":"10.1016\/j.dss.2019.05.004_bb0225","doi-asserted-by":"crossref","first-page":"631","DOI":"10.1109\/TCSVT.2013.2280061","article-title":"Adaptive sparse representations for video anomaly detection","volume":"24","author":"Mo","year":"2014","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10.1016\/j.dss.2019.05.004_bb0230","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1016\/j.knosys.2012.10.001","article-title":"Feature selection using dynamic weights for classification","volume":"37","author":"Sun","year":"2013","journal-title":"Knowledge-Based Systems"},{"key":"10.1016\/j.dss.2019.05.004_bb0235","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1016\/j.neucom.2004.01.194","article-title":"Effective feature selection scheme using mutual information","volume":"63","author":"Huang","year":"2005","journal-title":"Neurocomputing"},{"key":"10.1016\/j.dss.2019.05.004_bb0240","series-title":"Proceedings of the 19th ACM International Conference on Information and Knowledge Management, CIKM\u201904","first-page":"342","article-title":"Feature selection with conditional mutual information maximin in text categorization","author":"Wang","year":"2004"},{"key":"10.1016\/j.dss.2019.05.004_bb0245","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1023\/A:1022689900470","article-title":"Instance-based learning algorithms","volume":"6","author":"Aha","year":"1991","journal-title":"Machine Learning"},{"key":"10.1016\/j.dss.2019.05.004_bb0250","series-title":"Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations","author":"Witten","year":"2000"},{"issue":"1","key":"10.1016\/j.dss.2019.05.004_bb0255","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Machine Learning"},{"issue":"26","key":"10.1016\/j.dss.2019.05.004_bb0260","doi-asserted-by":"crossref","first-page":"15149","DOI":"10.1073\/pnas.211566398","article-title":"Multiclass cancer diagnosis using tumor gene expression signatures","volume":"98","author":"Ramaswamy","year":"2001","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"}],"container-title":["Decision Support Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167923619300806?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167923619300806?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T09:00:58Z","timestamp":1759136458000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0167923619300806"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":52,"alternative-id":["S0167923619300806"],"URL":"https:\/\/doi.org\/10.1016\/j.dss.2019.05.004","relation":{},"ISSN":["0167-9236"],"issn-type":[{"value":"0167-9236","type":"print"}],"subject":[],"published":{"date-parts":[[2019,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Feature assessment and ranking for classification with nonlinear sparse representation and approximate dependence analysis","name":"articletitle","label":"Article Title"},{"value":"Decision Support Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dss.2019.05.004","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"113064"}}