{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T16:11:26Z","timestamp":1771517486493,"version":"3.50.1"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62076089"],"award-info":[{"award-number":["62076089"]}],"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":["61976082"],"award-info":[{"award-number":["61976082"]}],"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":["61976120"],"award-info":[{"award-number":["61976120"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2023,2]]},"DOI":"10.1007\/s13042-022-01653-0","type":"journal-article","created":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T09:05:02Z","timestamp":1664960702000},"page":"609-631","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["TSFNFS: two-stage-fuzzy-neighborhood feature selection with binary whale optimization algorithm"],"prefix":"10.1007","volume":"14","author":[{"given":"Lin","family":"Sun","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinya","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiping","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiucheng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huili","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,10,5]]},"reference":[{"key":"1653_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116187","volume":"190","author":"X Zhang","year":"2022","unstructured":"Zhang X, Yao Y (2022) Tri-level attribute reduction in rough set theory. Expert Syst Appl 190:116187","journal-title":"Expert Syst Appl"},{"issue":"6","key":"1653_CR2","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1109\/TFUZZ.2020.2975152","volume":"29","author":"W Ding","year":"2021","unstructured":"Ding W, Pedrycz W, Triguero I, Cao Z, Lin C (2021) Multigranulation supertrust model for attribute reduction. IEEE Trans Fuzzy Syst 29(6):1395\u20131408","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"1653_CR3","doi-asserted-by":"publisher","first-page":"2345","DOI":"10.1007\/s13042-022-01528-4","volume":"13","author":"W Qian","year":"2022","unstructured":"Qian W, Dong P, Wang Y, Dai S, Huang J (2022) Local rough set-based feature selection for label distribution learning with incomplete labels. Int J Mach Learn Cybern 13:2345\u20132364","journal-title":"Int J Mach Learn Cybern"},{"key":"1653_CR4","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.ins.2019.05.072","volume":"502","author":"L Sun","year":"2019","unstructured":"Sun L, Zhang X, Qian Y, Xu J, Zhang S (2019) Feature selection using neighborhood entropy-based uncertainty measures for gene expression data classification. Inf Sci 502:18\u201341","journal-title":"Inf Sci"},{"key":"1653_CR5","doi-asserted-by":"publisher","first-page":"724","DOI":"10.1016\/j.ins.2022.08.118","volume":"612","author":"L Sun","year":"2022","unstructured":"Sun L, Li M, Ding W, Zhang E, Mu X, Xu J (2022) AFNFS: Adaptive fuzzy neighborhood-based feature selection with adaptive synthetic over-sampling for imbalanced data. Inf Sci 612:724\u2013744","journal-title":"Inf Sci"},{"issue":"8","key":"1653_CR6","doi-asserted-by":"publisher","first-page":"9148","DOI":"10.1007\/s10489-021-02861-x","volume":"52","author":"W Xu","year":"2022","unstructured":"Xu W, Yuan K, Li W (2022) Dynamic updating approximations of local generalized multigranulation neighborhood rough set. Appl Intell 52(8):9148\u20139173","journal-title":"Appl Intell"},{"issue":"4","key":"1653_CR7","first-page":"152","volume":"49","author":"L Sun","year":"2022","unstructured":"Sun L, Huang M, Xu J (2022) Weak label feature selection method based on neighborhood rough sets and Relief. Chin Comput Sci 49(4):152\u2013160","journal-title":"Chin Comput Sci"},{"key":"1653_CR8","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1016\/j.ijar.2022.05.004","volume":"147","author":"C Zhang","year":"2022","unstructured":"Zhang C, Ding J, Zhan J, Li D (2022) Incomplete three-way multi-attribute group decision making based on adjustable multigranulation Pythagorean fuzzy probabilistic rough sets. Int J Approx Reason 147:40\u201359","journal-title":"Int J Approx Reason"},{"key":"1653_CR9","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1016\/j.ins.2019.01.033","volume":"507","author":"C Zhang","year":"2020","unstructured":"Zhang C, Li D, Liang J (2020) Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes. Inf Sci 507:665\u2013683","journal-title":"Inf Sci"},{"key":"1653_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109849","volume":"256","author":"L Sun","year":"2022","unstructured":"Sun L, Wang X, Ding W, Xu J (2022) TSFNFR: Two-stage fuzzy neighborhood-based feature reduction with\nbinary whale optimization algorithm for imbalanced data classification. Knowl Based Syst 256:109849","journal-title":"Knowl Based Syst"},{"key":"1653_CR11","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1016\/j.ins.2022.02.004","volume":"593","author":"L Sun","year":"2022","unstructured":"Sun L, Zhang J, Ding W, Xu J (2022) Feature reduction for imbalanced data classification using similarity-based feature clustering with adaptive weighted k-nearest neighbors. Inf Sci 593:591\u2013613","journal-title":"Inf Sci"},{"issue":"1","key":"1653_CR12","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1109\/TFUZZ.2020.2989098","volume":"29","author":"L Sun","year":"2021","unstructured":"Sun L, Wang L, Ding W, Qian Y, Xu J (2021) Feature selection using fuzzy neighborhood entropy-based uncertainty measures for fuzzy neighborhood multigranulation rough sets. IEEE Trans Fuzzy Syst 29(1):19\u201333","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"4","key":"1653_CR13","doi-asserted-by":"publisher","first-page":"5731","DOI":"10.3233\/JIFS-181904","volume":"37","author":"L Sun","year":"2019","unstructured":"Sun L, Wang W, Xu J, Zhang S (2019) Improved LLE and neighborhood rough sets-based gene selection using Lebesgue measure for cancer classification on gene expression data. J Intell Fuzzy Syst 37(4):5731\u20135742","journal-title":"J Intell Fuzzy Syst"},{"key":"1653_CR14","doi-asserted-by":"publisher","first-page":"1550","DOI":"10.1016\/j.ins.2022.05.122","volume":"607","author":"X Zhang","year":"2022","unstructured":"Zhang X, Jiang J (2022) Measurement, modeling, reduction of decision-theoretic multigranulation fuzzy rough sets based on three-way decisions. Inf Sci 607:1550\u20131582","journal-title":"Inf Sci"},{"key":"1653_CR15","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.knosys.2012.06.010","volume":"36","author":"L Sun","year":"2012","unstructured":"Sun L, Xu J, Tian Y (2012) Feature selection using rough entropy-based uncertainty measures in incomplete decision systems. Knowl Based Syst 36:206\u2013216","journal-title":"Knowl Based Syst"},{"key":"1653_CR16","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3171784","author":"W Xu","year":"2022","unstructured":"Xu W, Yuan K, Li W, Ding W (2022) An emerging fuzzy feature selection method using composite entropy-based uncertainty measure and data distribution. IEEE Trans Emerg Top Comput Intell. https:\/\/doi.org\/10.1109\/TETCI.2022.3171784","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"issue":"2","key":"1653_CR17","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1109\/TCYB.2014.2361772","volume":"46","author":"W Xu","year":"2016","unstructured":"Xu W, Li W (2016) Granular computing approach to two-way learning based on formal concept analysis in fuzzy datasets. IEEE Trans Cybern 46(2):366\u2013379","journal-title":"IEEE Trans Cybern"},{"key":"1653_CR18","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3184120","author":"W Li","year":"2022","unstructured":"Li W, Zhou H, Xu W, Wang X, Pedrycz W (2022) Interval dominance-based feature selection for interval-valued ordered data. IEEE Trans Neural Netw Learn Syst. https:\/\/doi.org\/10.1109\/TNNLS.2022.3184120","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"5","key":"1653_CR19","doi-asserted-by":"publisher","first-page":"1197","DOI":"10.1109\/TFUZZ.2021.3053844","volume":"30","author":"L Sun","year":"2022","unstructured":"Sun L, Yin T, Ding W, Qian Y, Xu J (2022) Feature selection with missing labels using multilabel fuzzy neighborhood rough sets and maximum relevance minimum redundancy. IEEE Trans Fuzzy Syst 30(5):1197\u20131211","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"1653_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105373","volume":"192","author":"L Sun","year":"2020","unstructured":"Sun L, Wang L, Ding W, Qian Y, Xu J (2020) Neighborhood multi-granulation rough sets-based attribute reduction using Lebesgue and entropy measures in incomplete neighborhood decision systems. Knowl Based Syst 192:105373","journal-title":"Knowl Based Syst"},{"key":"1653_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.104942","volume":"186","author":"L Sun","year":"2019","unstructured":"Sun L, Wang L, Qian Y, Xu J, Zhang S (2019) Feature selection using Lebesgue and entropy measures for incomplete neighborhood decision systems. Knowl Based Syst 186:104942","journal-title":"Knowl Based Syst"},{"key":"1653_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.105516","volume":"194","author":"W Shu","year":"2020","unstructured":"Shu W, Qian W, Xie Y (2020) Incremental feature selection for dynamic hybrid data using neighborhood rough set. Knowl Based Syst 194:105516","journal-title":"Knowl Based Syst"},{"issue":"1","key":"1653_CR23","doi-asserted-by":"publisher","first-page":"572","DOI":"10.2991\/ijcis.d.210106.003","volume":"14","author":"Y Chen","year":"2021","unstructured":"Chen Y, Chen Y (2021) Feature subset selection based on variable precision neighborhood rough sets. Int J Comput Intell Syst 14(1):572\u2013581","journal-title":"Int J Comput Intell Syst"},{"issue":"3","key":"1653_CR24","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1109\/TFUZZ.2018.2862870","volume":"27","author":"A Tan","year":"2019","unstructured":"Tan A, Wu W, Qian Y, Liang J, Chen J, Li J (2019) Intuitionistic fuzzy rough set-based granular structures and attribute subset selection. IEEE Trans Fuzzy Syst 27(3):527\u2013539","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"6","key":"1653_CR25","doi-asserted-by":"publisher","first-page":"2288","DOI":"10.3390\/e15062288","volume":"15","author":"K Zeng","year":"2013","unstructured":"Zeng K, She K, Niu X (2013) Multi-granulation entropy and its applications. Entropy 15(6):2288\u20132302","journal-title":"Entropy"},{"issue":"5","key":"1653_CR26","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1109\/TFUZZ.2013.2291570","volume":"22","author":"D Chen","year":"2014","unstructured":"Chen D, Yang Y (2014) Attribute reduction for heterogeneous data based on the combination of classical and fuzzy rough set models. IEEE Trans Fuzzy Syst 22(5):1325\u20131334","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"1653_CR27","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1016\/j.knosys.2016.08.009","volume":"111","author":"C Wang","year":"2016","unstructured":"Wang C, Shao M, He Q, Qian Y, Qi Y (2016) Feature subset selection based on fuzzy neighborhood rough sets. Knowl Based Syst 111:173\u2013179","journal-title":"Knowl Based Syst"},{"key":"1653_CR28","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.patrec.2021.03.001","volume":"146","author":"X Zhang","year":"2021","unstructured":"Zhang X, Fan Y, Yang J (2021) Feature selection based on fuzzy-neighborhood relative decision entropy. Pattern Recogn Lett 146:100\u2013107","journal-title":"Pattern Recogn Lett"},{"issue":"1","key":"1653_CR29","doi-asserted-by":"publisher","first-page":"117","DOI":"10.3233\/JIFS-18100","volume":"36","author":"J Xu","year":"2019","unstructured":"Xu J, Wang Y, Mu H, Huang F (2019) Feature genes selection based on fuzzy neighborhood conditional entropy. J Intell Fuzzy Syst 36(1):117\u2013126","journal-title":"J Intell Fuzzy Syst"},{"key":"1653_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03554-9","author":"L Sun","year":"2022","unstructured":"Sun L, Si S, Zhao J, Xu J, Lin Y, Lv Z (2022) Feature selection using binary monarch butterfly optimization. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-022-03554-9","journal-title":"Appl Intell"},{"issue":"1","key":"1653_CR31","first-page":"87","volume":"47","author":"X Fan","year":"2020","unstructured":"Fan X, Chen H (2020) Stepwise optimized feature selection algorithm based on discernibility matrix and mRMR. Chin Comput Sci 47(1):87\u201395","journal-title":"Chin Comput Sci"},{"key":"1653_CR32","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili S, Lewis A (2016) The whale optimization algorithm. Adv Eng Softw 95:51\u201367","journal-title":"Adv Eng Softw"},{"issue":"10","key":"1653_CR33","first-page":"67","volume":"48","author":"M Tian","year":"2021","unstructured":"Tian M, Liang X, Fu X, Sun Y, Li Z (2021) Multi-subgroup particle swarm optimization with game probability selection. Chin Comput Sci 48(10):67\u201376","journal-title":"Chin Comput Sci"},{"key":"1653_CR34","doi-asserted-by":"publisher","first-page":"8978","DOI":"10.1038\/s41598-019-45223-x","volume":"9","author":"L Sun","year":"2019","unstructured":"Sun L, Kong X, Xu J, Xue Z, Zhai R, Zhang S (2019) A hybrid gene selection method based on ReliefF and Ant Colony Optimization algorithm for tumor classification. Sci Rep 9:8978","journal-title":"Sci Rep"},{"key":"1653_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107543","volume":"233","author":"C Sanjoy","year":"2021","unstructured":"Sanjoy C, Apu K, Ratul C, Moumita S (2021) An enhanced whale optimization algorithm for large scale optimization problems. Knowl Based Syst 233:107543","journal-title":"Knowl Based Syst"},{"key":"1653_CR36","doi-asserted-by":"publisher","first-page":"14908","DOI":"10.1109\/ACCESS.2018.2879848","volume":"7","author":"Y Zheng","year":"2019","unstructured":"Zheng Y, Li Y, Wang G, Chen Y, Xu Q, Fan J, Cui X (2019) A novel hybrid algorithm for feature selection based on whale optimization algorithm. IEEE Access 7:14908\u201314923","journal-title":"IEEE Access"},{"key":"1653_CR37","doi-asserted-by":"publisher","first-page":"3527","DOI":"10.1007\/s12652-020-02592-w","volume":"12","author":"U Moorthy","year":"2021","unstructured":"Moorthy U, Gandhi U (2021) A novel optimal feature selection technique for medical data classification using ANOVA based whale optimization. J Ambient Intell Humaniz Comput 12:3527\u20133538","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"3","key":"1653_CR38","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1007\/s13042-019-00996-5","volume":"11","author":"M Tawhid","year":"2020","unstructured":"Tawhid M, Ibrahim A (2020) Feature selection based on rough set approach, wrapper approach, and binary whale optimization algorithm. Int J Mach Learn Cybern 11(3):573\u2013602","journal-title":"Int J Mach Learn Cybern"},{"issue":"2","key":"1653_CR39","first-page":"44","volume":"47","author":"S Wang","year":"2020","unstructured":"Wang S, Chen H (2020) Feature selection method based on rough sets and improved whale optimization algorithm. Chin Comput Sci 47(2):44\u201350","journal-title":"Chin Comput Sci"},{"key":"1653_CR40","doi-asserted-by":"publisher","first-page":"6773","DOI":"10.1002\/int.22861","volume":"37","author":"L Sun","year":"2022","unstructured":"Sun L, Wang T, Ding W, Xu J, Tan A (2022) Two-stage-neighborhood-based multilabel classification for incomplete data with missing labels. Int J Intell Syst 37:6773\u20136810","journal-title":"Int J Intell Syst"},{"key":"1653_CR41","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-03142-3","author":"L Sun","year":"2022","unstructured":"Sun L, Zhang J, Ding W, Xu J (2022) Mixed measure-based feature selection using the Fisher score and neighborhood rough sets. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-021-03142-3","journal-title":"Appl Intell"},{"issue":"7","key":"1653_CR42","first-page":"157","volume":"46","author":"B Fang","year":"2019","unstructured":"Fang B, Chen H, Wang S (2019) Feature selection algorithm based on rough sets and fruit fly optimization. Chin Comput Sci 46(7):157\u2013164","journal-title":"Chin Comput Sci"},{"key":"1653_CR43","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.neucom.2021.12.019","volume":"473","author":"L Sun","year":"2022","unstructured":"Sun L, Qin X, Ding W, Xu J (2022) Nearest neighbors-based adaptive density peaks clustering with optimized allocation strategy. Neurocomputing 473:159\u2013181","journal-title":"Neurocomputing"},{"issue":"7","key":"1653_CR44","doi-asserted-by":"publisher","first-page":"1913","DOI":"10.1007\/s13042-021-01284-x","volume":"12","author":"L Sun","year":"2021","unstructured":"Sun L, Qin X, Ding W, Xu J, Zhang S (2021) Density peaks clustering based on k-nearest neighbors and self-recommendation. Int J Mach Learn Cybern 12(7):1913\u20131938","journal-title":"Int J Mach Learn Cybern"},{"issue":"4","key":"1653_CR45","doi-asserted-by":"publisher","first-page":"1245","DOI":"10.1007\/s10489-018-1320-1","volume":"49","author":"L Sun","year":"2019","unstructured":"Sun L, Zhang X, Qian Y, Xu J, Zhang S, Tian Y (2019) Joint neighborhood entropy-based gene selection method with fisher score for tumor classification. Appl Intell 49(4):1245\u20131259","journal-title":"Appl Intell"},{"key":"1653_CR46","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.jbi.2017.02.007","volume":"67","author":"Y Chen","year":"2017","unstructured":"Chen Y, Zhang Z, Zheng J, Ma Y, Xue Y (2017) Gene selection for tumor classification using neighborhood rough sets and entropy measures. J Biomed Inform 67:59\u201368","journal-title":"J Biomed Inform"},{"issue":"6","key":"1653_CR47","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1016\/j.camwa.2008.10.027","volume":"57","author":"F Xu","year":"2009","unstructured":"Xu F, Miao D, Wei L (2009) Fuzzy-rough attribute reduction via mutual information with an application to cancer classification. Comput Math Appl 57(6):1010\u20131017","journal-title":"Comput Math Appl"},{"key":"1653_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105190","volume":"191","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A, Heidarinejad M, Stephens B, Mirjalili S (2020) Equilibrium optimizer: a novel optimization algorithm. Knowl Based Syst 191:105190","journal-title":"Knowl Based Syst"},{"key":"1653_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113377","volume":"152","author":"A Faramaizi","year":"2020","unstructured":"Faramaizi A, Heidarinejad M, Mirjalili S, Gandomi A (2020) Marine predators algorithm: a nature-inspired metaheuristic. Expert Syst Appl 152:113377","journal-title":"Expert Syst Appl"},{"issue":"3","key":"1653_CR50","first-page":"243","volume":"6","author":"S Bozorgi","year":"2019","unstructured":"Bozorgi S, Yazdani S (2019) IWOA: an improved whale optimization algorithm for optimization problems. J Comput Des Eng 6(3):243\u2013259","journal-title":"J Comput Des Eng"},{"key":"1653_CR51","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-020-01189-3","author":"Q Fan","year":"2020","unstructured":"Fan Q, Chen Z, Zhang W, Fang X (2020) ESSAWOA: enhanced whale optimization algorithm integrated with Salp Swarm Algorithm for global optimization. Eng Comput. https:\/\/doi.org\/10.1007\/s00366-020-01189-3","journal-title":"Eng Comput"},{"key":"1653_CR52","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03304-8","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Saha A, Sharma S, Chakraborty R, Debnath S (2021) A hybrid whale optimization algorithm for global optimization. J Ambient Intell Humaniz Comput. https:\/\/doi.org\/10.1007\/s12652-021-03304-8","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"5","key":"1653_CR53","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1016\/j.patrec.2005.09.004","volume":"27","author":"Q Hu","year":"2006","unstructured":"Hu Q, Yu D, Xie Z (2006) Information-preserving hybrid data reduction based on fuzzy-rough techniques. Pattern Recogn Lett 27(5):414\u2013423","journal-title":"Pattern Recogn Lett"},{"key":"1653_CR54","doi-asserted-by":"publisher","first-page":"887","DOI":"10.1016\/j.ins.2021.08.032","volume":"578","author":"L Sun","year":"2021","unstructured":"Sun L, Wang T, Ding W, Xu J, Lin Y (2021) Feature selection using Fisher score and multilabel neighborhood rough sets for multilabel classification. Inf Sci 578:887\u2013912","journal-title":"Inf Sci"},{"issue":"3","key":"1653_CR55","doi-asserted-by":"publisher","first-page":"2105","DOI":"10.1007\/s40747-021-00636-y","volume":"8","author":"J Xu","year":"2022","unstructured":"Xu J, Shen K, Sun L (2022) Multi-label feature selection based on fuzzy neighborhood rough sets. Complex Intell Syst 8(3):2105\u20132129","journal-title":"Complex Intell Syst"},{"key":"1653_CR56","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/j.ins.2020.05.102","volume":"537","author":"L Sun","year":"2020","unstructured":"Sun L, Yin T, Ding W, Qian Y, Xu J (2020) Multilabel feature selection using ML-ReliefF and neighborhood mutual information for multilabel neighborhood decision systems. Inf Sci 537:401\u2013424","journal-title":"Inf Sci"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01653-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-022-01653-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-022-01653-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T09:03:28Z","timestamp":1674637408000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-022-01653-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,5]]},"references-count":56,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["1653"],"URL":"https:\/\/doi.org\/10.1007\/s13042-022-01653-0","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,5]]},"assertion":[{"value":"15 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 September 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 October 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}