{"id":"https://openalex.org/W2170406903","doi":"https://doi.org/10.5555/1390681.1390699","title":"An Information Criterion for Variable Selection in Support Vector Machines","display_name":"An Information Criterion for Variable Selection in Support Vector Machines","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2170406903","doi":"https://doi.org/10.5555/1390681.1390699","mag":"2170406903"},"language":"en","primary_location":{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/120603","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/120603","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"DTEW - KBI_0703, (1-33)","raw_type":"info:eu-repo/semantics/report"},"type":"report","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://lirias.kuleuven.be/handle/123456789/120603","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011502307","display_name":"Gerda Claeskens","orcid":"https://orcid.org/0000-0002-3863-5197"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gerda Claeskens","raw_affiliation_strings":["University of Toronto"],"raw_orcid":"https://orcid.org/0000-0002-3863-5197","affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025083815","display_name":"Christophe Croux","orcid":"https://orcid.org/0000-0003-2912-3437"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Christophe Croux","raw_affiliation_strings":["University of Toronto"],"raw_orcid":"https://orcid.org/0000-0003-2912-3437","affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039481914","display_name":"Johan Van Kerckhoven","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Johan Van Kerckhoven","raw_affiliation_strings":["Univ. of Cambridge"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Univ. of Cambridge","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"18","first_page":"541","last_page":"558"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7584274411201477},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6865681409835815},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6757979989051819},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.673022985458374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6559107303619385},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.6202842593193054},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5754107236862183},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5739064812660217},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5434553623199463},{"id":"https://openalex.org/keywords/relevance-vector-machine","display_name":"Relevance vector machine","score":0.46601253747940063},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46259182691574097},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43378469347953796},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42864561080932617},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.428127646446228},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2179921567440033}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7584274411201477},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6865681409835815},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6757979989051819},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.673022985458374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6559107303619385},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.6202842593193054},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5754107236862183},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5739064812660217},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5434553623199463},{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.46601253747940063},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46259182691574097},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43378469347953796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42864561080932617},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.428127646446228},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2179921567440033},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/120603","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/120603","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"DTEW - KBI_0703, (1-33)","raw_type":"info:eu-repo/semantics/report"},{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/163816","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/163816","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Journal of Machine Learning Research, vol. 9, (541-558)","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.210.6913","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.210.6913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.jmlr.org/papers/volume9/claeskens08a/claeskens08a.pdf","raw_type":"text"},{"id":"mag:2170406903","is_oa":false,"landing_page_url":"http://feb.kuleuven.be/public/ndbae06/PDF-FILES/SVMartikelFinal.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419146","display_name":"International Conference on Artificial Intelligence and Statistics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"International Conference on Artificial Intelligence and Statistics","raw_type":null}],"best_oa_location":{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/120603","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/120603","pdf_url":null,"source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"DTEW - KBI_0703, (1-33)","raw_type":"info:eu-repo/semantics/report"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W53188351","https://openalex.org/W196162695","https://openalex.org/W1530699444","https://openalex.org/W1533169541","https://openalex.org/W1540007258","https://openalex.org/W1554944419","https://openalex.org/W1563088657","https://openalex.org/W1567323455","https://openalex.org/W1635526310","https://openalex.org/W1676930015","https://openalex.org/W1746819321","https://openalex.org/W1905898145","https://openalex.org/W1922017469","https://openalex.org/W1981890344","https://openalex.org/W1983655951","https://openalex.org/W2005201432","https://openalex.org/W2027363570","https://openalex.org/W2029096800","https://openalex.org/W2037491422","https://openalex.org/W2037984448","https://openalex.org/W2048716124","https://openalex.org/W2049353177","https://openalex.org/W2058815839","https://openalex.org/W2059448777","https://openalex.org/W2060161465","https://openalex.org/W2080726496","https://openalex.org/W2091467189","https://openalex.org/W2115729631","https://openalex.org/W2116948717","https://openalex.org/W2118142823","https://openalex.org/W2119479037","https://openalex.org/W2121241734","https://openalex.org/W2127972252","https://openalex.org/W2130698119","https://openalex.org/W2136796925","https://openalex.org/W2143426320","https://openalex.org/W2144898279","https://openalex.org/W2154053567","https://openalex.org/W2159706540","https://openalex.org/W2166381300","https://openalex.org/W2168175751","https://openalex.org/W2519828108","https://openalex.org/W3023786531","https://openalex.org/W3037265734"],"related_works":["https://openalex.org/W2143426320","https://openalex.org/W3123293388","https://openalex.org/W2135046866","https://openalex.org/W2168175751","https://openalex.org/W2148603752","https://openalex.org/W2119479037","https://openalex.org/W2134117233","https://openalex.org/W2017337590","https://openalex.org/W1560724230","https://openalex.org/W2053061982","https://openalex.org/W2769791993","https://openalex.org/W2080905836","https://openalex.org/W1607624180","https://openalex.org/W2416368433","https://openalex.org/W2156909104","https://openalex.org/W2106221629","https://openalex.org/W2130346227","https://openalex.org/W2995576761","https://openalex.org/W2157930875","https://openalex.org/W1661660971"],"abstract_inverted_index":{"Support":[0],"vector":[1,53],"machines":[2],"for":[3,108],"classification":[4],"have":[5],"the":[6,9,23,26,48,51,57,61,85,105],"advantage":[7],"that":[8,19,84],"curse":[10],"of":[11,22,25,50,60,92],"dimensionality":[12],"is":[13],"circumvented.":[14],"It":[15],"has":[16],"been":[17],"shown":[18],"a":[20,77],"reduction":[21],"dimension":[24],"input":[27],"space":[28],"leads":[29],"to":[30,71,100],"even":[31],"better":[32],"results.":[33],"For":[34],"this":[35],"purpose,":[36],"we":[37],"propose":[38],"two":[39],"information":[40],"criteria":[41,67,87],"which":[42],"can":[43],"be":[44],"computed":[45],"directly":[46],"from":[47],"definition":[49],"support":[52],"machine.":[54],"We":[55,102],"assess":[56],"predictive":[58],"performance":[59],"models":[62],"selected":[63],"by":[64],"our":[65],"new":[66,86],"and":[68],"compare":[69],"them":[70],"existing":[72],"variable":[73],"selection":[74],"techniques":[75],"in":[76,90],"simulation":[78,81],"study.":[79],"The":[80],"results":[82],"show":[83],"are":[88],"competitive":[89],"terms":[91],"generalization":[93],"error":[94],"rate":[95],"while":[96],"being":[97],"much":[98],"easier":[99],"compute.":[101],"arrive":[103],"at":[104],"same":[106],"findings":[107],"comparison":[109],"on":[110],"some":[111],"real-world":[112],"benchmark":[113],"data":[114],"sets.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}