{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:16:45Z","timestamp":1740133005873,"version":"3.37.3"},"reference-count":77,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/501100002491","name":"Hansung University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002491","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2016,1,1]]},"DOI":"10.1109\/tkde.2015.2458867","type":"journal-article","created":{"date-parts":[[2015,7,21]],"date-time":"2015-07-21T14:46:18Z","timestamp":1437489978000},"page":"29-40","source":"Crossref","is-referenced-by-count":15,"title":["Booster in High Dimensional Data Classification"],"prefix":"10.1109","volume":"28","author":[{"given":"HyunJi","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byong Su","family":"Choi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Moon Yul","family":"Huh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72523-7_28"},{"journal-title":"Data Mining-Practical Machine Learning Tools and Techniques with JAVA Implementations","year":"2000","author":"witten","key":"ref72"},{"journal-title":"Modern Applied Statistics with S","year":"2003","author":"venables","key":"ref71"},{"key":"ref70","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1038\/415530a","article-title":"Gene expression profiling predicts clinical outcome of breast cancer","volume":"415","author":"veer","year":"2002","journal-title":"Nature"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1016\/S1535-6108(02)00032-6"},{"key":"ref77","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":"ref74","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg210"},{"key":"ref39","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s00521-013-1368-0","article-title":"A review of feature selection methods based on mutual information","volume":"24","author":"jorge","year":"2014","journal-title":"Neural Comput Appl"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2013.01.021"},{"key":"ref38","first-page":"338","article-title":"Estimating continuous distributions in Bayesian classifiers","author":"john","year":"0","journal-title":"Proc 11th Conf Uncertainty Artif Intell"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2008.08.001"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.01.023"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbn005"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiolchem.2010.07.002"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/B978-1-55860-335-6.50023-4"},{"article-title":"mRMRe: An R package for parallelized mRMR ensemble feature selection","year":"2012","author":"jay","key":"ref36"},{"key":"ref35","article-title":"An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors","volume":"6","author":"jafari","year":"2006","journal-title":"BMC Med Inf Decision Making"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2008.02.003"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1016\/S1535-6108(02)00030-2"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.181"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.34"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.191367098"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1002\/sam.11152"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1038\/nm1556"},{"article-title":"Correlation-based feature selection for machine learning","year":"1999","author":"hall","key":"ref27"},{"key":"ref65","first-page":"337","article-title":"An experimental study of methods combining multiple classifiers-diversified both by feature selection and bootstrap sampling","author":"stefanowski","year":"2005","journal-title":"Issues Representation Process Uncertain Imprecise Inf"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.012025199"},{"key":"ref29","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","author":"hastie","year":"2009","journal-title":"The Elements of Statistical Learning"},{"key":"ref67","doi-asserted-by":"crossref","first-page":"1610","DOI":"10.1109\/TPAMI.2009.190","article-title":"Local-learning-based feature selection for high-dimensional data analysis","volume":"32","author":"sun","year":"2010","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-010-5224-5"},{"key":"ref69","article-title":"The information bottleneck method","author":"tishby","year":"0","journal-title":"Proc 37th Annu Allerton Conf Commun Control Comput"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00153759"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp630"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2012.12.051"},{"key":"ref22","first-page":"531","article-title":"Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring","volume":"286","author":"golub","year":"1999","journal-title":"Amer Assoc Advancement Sci"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1158\/0008-5472.CAN-04-0452"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04180-8_47"},{"key":"ref23","first-page":"4963","article-title":"Translation of microarray data into clinically relevant cancer diagnostic tests using gene expression ratios in lung cancer and mesothelioma","volume":"62","author":"gordon","year":"2002","journal-title":"Cancer Res"},{"key":"ref26","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"guyon","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"ref25","first-page":"2298","article-title":"Proteomic analysis of lung adenocarcinoma: Identification of a highly expressed set of proteins in tumors","volume":"8","author":"guoan","year":"2002","journal-title":"Clinical Cancer Res"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2005.159"},{"key":"ref51","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/415436a","article-title":"Prediction of central nervous system embryonal tumour outcome based on gene expression","volume":"415","author":"scott","year":"2002","journal-title":"Nature"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.4161\/cbt.2.4.431"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2005.03.026"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-3324-9"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72523-7_27"},{"journal-title":"Multivariate Density Estimation Theory Practice and Visualization","year":"2009","author":"scott","key":"ref55"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1093\/hmg\/ddq567"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btm344"},{"year":"0","key":"ref52"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1137\/1.9780898717693"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pgen.1000602"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-006-0040-8"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"corinna","year":"1995","journal-title":"Mach Learn"},{"journal-title":"Elements of Information Theory","year":"2002","author":"cover","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.3390\/microarrays2020115"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2013.07.012"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1214\/07-AOS504"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1198\/016214507000000969"},{"key":"ref18","first-page":"1022","article-title":"Multi-interval discretization of continuous-valued attributes for classification learning","volume":"13","author":"fayyad","year":"1993","journal-title":"Artif Intell"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2012.05.019"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/35000501"},{"article-title":"On feature selection stability: A data perspective","year":"2013","author":"alelyan","key":"ref3"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.08.051"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.96.12.6745"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1214\/10-AOS799"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3150\/bj\/1106314847"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2008.923858"},{"key":"ref9","first-page":"27","article-title":"Conditional likelihood maximization: A unifying framework for information theoretic feature selection","volume":"13","author":"brown","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref46","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1023\/A:1025667309714","article-title":"Theoretical and empirical analysis of ReliefF and RReliefF","volume":"53","author":"marko","year":"2003","journal-title":"Machine Learning"},{"key":"ref45","first-page":"907","article-title":"Forest density estimation","volume":"12","author":"liu","year":"2011","journal-title":"Journal of Machine Learning Research"},{"article-title":"e1071: Misc functions of the department of statistics (e1071), TU Wien","year":"2012","author":"meyer","key":"ref48"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2010.00740.x"},{"key":"ref42","first-page":"284","article-title":"Toward optimal feature selection","author":"koller","year":"0","journal-title":"Proc 13th Int Conf Mach Learn"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.csda.2004.07.026"},{"key":"ref44","first-page":"51","article-title":"A comparative study on feature selection and classification methods using gene expression profiles and proteomic patterns","volume":"13","author":"liu","year":"2002","journal-title":"Genome Informatics Series"},{"key":"ref43","first-page":"421","article-title":"A stability index for feature selection","author":"kuncheva","year":"0","journal-title":"Appl Artif Intell"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/7347496\/7163594.pdf?arnumber=7163594","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:46:05Z","timestamp":1641987965000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7163594\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,1]]},"references-count":77,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2015.2458867","relation":{},"ISSN":["1041-4347"],"issn-type":[{"type":"print","value":"1041-4347"}],"subject":[],"published":{"date-parts":[[2016,1,1]]}}}