{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T18:28:11Z","timestamp":1725733691548},"reference-count":42,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2016,7,1]],"date-time":"2016-07-01T00:00:00Z","timestamp":1467331200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Fusion"],"published-print":{"date-parts":[[2016,7]]},"DOI":"10.1016\/j.inffus.2015.12.002","type":"journal-article","created":{"date-parts":[[2015,12,17]],"date-time":"2015-12-17T20:53:38Z","timestamp":1450385618000},"page":"69-79","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":35,"special_numbering":"C","title":["Fusion of instance selection methods in regression tasks"],"prefix":"10.1016","volume":"30","author":[{"given":"\u00c1lvar","family":"Arnaiz-Gonz\u00e1lez","sequence":"first","affiliation":[]},{"given":"Marcin","family":"Blachnik","sequence":"additional","affiliation":[]},{"given":"Miros\u0142aw","family":"Kordos","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-1206-1084","authenticated-orcid":false,"given":"C\u00e9sar","family":"Garc\u00eda-Osorio","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"2-3","key":"10.1016\/j.inffus.2015.12.002_bib0001","first-page":"255","article-title":"KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework","volume":"17","author":"Alcal\u00e1-Fdez","year":"2011","journal-title":"Mult. Valued L. Soft Comput."},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0002","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1109\/TFUZZ.2011.2173582","article-title":"Genetic training instance selection in multiobjective evolutionary fuzzy systems: a coevolutionary approach","volume":"20","author":"Antonelli","year":"2012","journal-title":"IEEE Trans. Fuzzy Syst."},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0003","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1145\/116873.116880","article-title":"Voronoi diagrams \u2014 a survey of a fundamental geometric data structure","volume":"23","author":"Aurenhammer","year":"1991","journal-title":"ACM Comput. Surv."},{"issue":"06","key":"10.1016\/j.inffus.2015.12.002_bib0004","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1142\/S0218001405004332","article-title":"Decision boundary preserving prototype selection for nearest neighbor classification","volume":"19","author":"Barandela","year":"2005","journal-title":"Int. J. Pattern Recognit. Artif. Intell."},{"key":"10.1016\/j.inffus.2015.12.002_bib0005","first-page":"40","article-title":"Bagging of instance selection algorithms","author":"Blachnik","year":"2014"},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0006","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/BF00058655","article-title":"Bagging predictors","volume":"24","author":"Breiman","year":"1996","journal-title":"Mach. Learn."},{"key":"10.1016\/j.inffus.2015.12.002_bib0007","series-title":"Proceedings of ACM SIGMOD International Conference on Management of Data (SIGMOD)","article-title":"LOF: identifying density-based local outliers","author":"Breunig","year":"2000"},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0008","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1023\/A:1014043630878","article-title":"Advances in instance selection for instance-based learning algorithms","volume":"6","author":"Brighton","year":"2002","journal-title":"Data Min. Knowl. Discov."},{"issue":"1","key":"10.1016\/j.inffus.2015.12.002_sbref0009","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1016\/j.inffus.2004.04.004","article-title":"Diversity creation methods: a survey and categorisation","volume":"6","author":"Brown","year":"2005","journal-title":"Inf. Fusion"},{"issue":"5-8","key":"10.1016\/j.inffus.2015.12.002_bib0010","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1007\/s00170-011-3300-z","article-title":"Avoiding neural network fine tuning by using ensemble learning: application to ball-end milling operations","volume":"57","author":"Bustillo","year":"2011","journal-title":"Int. J. Adv. Manuf. Technol."},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0011","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/S0304-4076(96)01818-0","article-title":"An R-squared measure of goodness of fit for some common nonlinear regression models","volume":"77","author":"Cameron","year":"1997","journal-title":"J. Econom."},{"key":"10.1016\/j.inffus.2015.12.002_bib0012","first-page":"125","article-title":"Information discovery through hierarchical maximum entropy discretization and synthesis","author":"David","year":"1991","journal-title":"Knowl. Discov. Databases"},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0013","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1109\/TPAMI.2011.142","article-title":"Prototype selection for nearest neighbor classification: taxonomy and empirical study","volume":"34","author":"Garcia","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"10","key":"10.1016\/j.inffus.2015.12.002_bib0014","doi-asserted-by":"crossref","first-page":"2044","DOI":"10.1016\/j.ins.2009.12.010","article-title":"Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power","volume":"180","author":"Garc\u00eda","year":"2010","journal-title":"Inf. Sci."},{"issue":"10-12","key":"10.1016\/j.inffus.2015.12.002_sbref0015","doi-asserted-by":"crossref","first-page":"2030","DOI":"10.1016\/j.neucom.2009.11.031","article-title":"New method for instance or prototype selection using mutual information in time series prediction","volume":"73","author":"Guillen","year":"2010","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.inffus.2015.12.002_bib0016","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1145\/1656274.1656278","article-title":"The WEKA data mining software: An update","volume":"11","author":"Hall","year":"2009","journal-title":"SIGKDD Explor. Newsl."},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0017","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1109\/TIT.1968.1054155","article-title":"The condensed nearest neighbor rule (corresp.)","volume":"14","author":"Hart","year":"1968","journal-title":"IEEE Trans. Inf. Theory"},{"key":"10.1016\/j.inffus.2015.12.002_bib0018","series-title":"RapidMiner: Data Mining Use Cases and Business Analytics Applications","author":"Hofmann","year":"2013"},{"key":"10.1016\/j.inffus.2015.12.002_bib0019","first-page":"598","article-title":"Comparison of instances seletion algorithms i. algorithms survey","author":"Jankowski","year":"2004"},{"key":"10.1016\/j.inffus.2015.12.002_bib0020","series-title":"Technical Report TKK-F-A601","article-title":"Learning vector quantization for pattern recognition","author":"Kohonen","year":"1986"},{"key":"10.1016\/j.inffus.2015.12.002_bib0021","first-page":"263","article-title":"Instance selection with neural networks for regression problems","author":"Kordos","year":"2012"},{"key":"10.1016\/j.inffus.2015.12.002_bib0022","first-page":"414","article-title":"Do we need whatever more than k-NN?","author":"Kordos","year":"2010"},{"key":"10.1016\/j.inffus.2015.12.002_bib0023","article-title":"Reducing noise impact on MLP training","author":"Kordos","year":"2015","journal-title":"Soft Comput."},{"key":"10.1016\/j.inffus.2015.12.002_bib0024","series-title":"Combining Pattern Classifiers: Methods and Algorithms","author":"Kuncheva","year":"2004"},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0025","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/TKDE.2014.2327034","article-title":"A set of complexity measures designed for applying meta-learning to instance selection","volume":"27","author":"Leyva","year":"2015","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"4","key":"10.1016\/j.inffus.2015.12.002_bib0026","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1016\/j.patcog.2014.10.001","article-title":"Three new instance selection methods based on local sets: a comparative study with several approaches from a bi-objective perspective","volume":"48","author":"Leyva","year":"2015","journal-title":"Pattern Recognit."},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0027","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1109\/TPAMI.2009.164","article-title":"Class conditional nearest neighbor for large margin instance selection","volume":"32","author":"Marchiori","year":"2010","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"10.1016\/j.inffus.2015.12.002_bib0028","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.inffus.2010.11.004","article-title":"Random feature weights for decision tree ensemble construction","volume":"13","author":"Maudes","year":"2012","journal-title":"Inf. Fusion"},{"issue":"2","key":"10.1016\/j.inffus.2015.12.002_bib0029","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1007\/s10462-010-9165-y","article-title":"A review of instance selection methods","volume":"34","author":"Olvera-L\u00f3pez","year":"2010","journal-title":"Artif. Intell. Rev."},{"key":"10.1016\/j.inffus.2015.12.002_bib0030","series-title":"Proceedings of IEEE International Conference on Data Engineering (ICDE)","article-title":"Loci: Fast outlier detection using the local correlation integral","author":"Papadimitriou","year":"2003"},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0031","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MCAS.2006.1688199","article-title":"Ensemble based systems in decision making","volume":"6","author":"Polikar","year":"2006","journal-title":"Circuits and Syst. Mag. IEEE"},{"issue":"4","key":"10.1016\/j.inffus.2015.12.002_bib0032","doi-asserted-by":"crossref","first-page":"1009","DOI":"10.1016\/S0031-3203(02)00119-X","article-title":"Finding representative patterns with ordered projections","volume":"36","author":"Riquelme","year":"2003","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.inffus.2015.12.002_bib0033","series-title":"Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ)","first-page":"1","article-title":"An instance selection algorithm for regression and its application in variance reduction","author":"Rodriguez-Fdez","year":"2013"},{"key":"10.1016\/j.inffus.2015.12.002_bib0034","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.inffus.2015.06.005","article-title":"Decision forest: twenty years of research","volume":"27","author":"Rokach","year":"2016","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.inffus.2015.12.002_bib0035","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.inffus.2015.04.002","article-title":"INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control","volume":"27","author":"S\u00e1ez","year":"2016","journal-title":"Inf. Fusion"},{"issue":"6","key":"10.1016\/j.inffus.2015.12.002_bib0036","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/S0167-8655(97)00035-4","article-title":"Prototype selection for the nearest neighbour rule through proximity graphs","volume":"18","author":"S\u00e1nchez","year":"1997","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.inffus.2015.12.002_bib0037","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.neucom.2014.03.006","article-title":"A methodology for training set instance selection using mutual information in time series prediction","volume":"141","author":"Stojanovi\u0107","year":"2014","journal-title":"Neurocomputing"},{"key":"10.1016\/j.inffus.2015.12.002_bib0038","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.neucom.2012.08.070","article-title":"Manifold-preserving graph reduction for sparse semi-supervised learning","volume":"124","author":"Sun","year":"2014","journal-title":"Neurocomputing"},{"issue":"8","key":"10.1016\/j.inffus.2015.12.002_bib0039","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1007\/s00500-003-0310-2","article-title":"Genetic algorithms for outlier detection and variable selection in linear regression models","volume":"8","author":"Tolvi","year":"2004","journal-title":"Soft Comput."},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0040","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1023\/A:1007626913721","article-title":"Reduction techniques for instance-based learning algorithms","volume":"38","author":"Wilson","year":"2000","journal-title":"Mach. Learn."},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0041","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1109\/TSMC.1972.4309137","article-title":"Asymptotic properties of nearest neighbor rules using edited data","volume":"SMC-2","author":"Wilson","year":"1972","journal-title":"IEEE Trans. Syst. Man Cybern."},{"issue":"3","key":"10.1016\/j.inffus.2015.12.002_bib0042","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.inffus.2011.03.007","article-title":"A measure of competence based on random classification for dynamic ensemble selection","volume":"13","author":"Woloszynski","year":"2012","journal-title":"Inf. Fusion"}],"container-title":["Information Fusion"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253515001141?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1566253515001141?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2018,9,16]],"date-time":"2018-09-16T17:55:43Z","timestamp":1537120543000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1566253515001141"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7]]},"references-count":42,"alternative-id":["S1566253515001141"],"URL":"https:\/\/doi.org\/10.1016\/j.inffus.2015.12.002","relation":{},"ISSN":["1566-2535"],"issn-type":[{"value":"1566-2535","type":"print"}],"subject":[],"published":{"date-parts":[[2016,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Fusion of instance selection methods in regression tasks","name":"articletitle","label":"Article Title"},{"value":"Information Fusion","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.inffus.2015.12.002","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"Copyright \u00a9 2015 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}