{"id":"https://openalex.org/W2593881748","doi":"https://doi.org/10.1142/s021821301760003x","title":"Induced Subgraph Game for Ensemble Selection","display_name":"Induced Subgraph Game for Ensemble Selection","publication_year":2017,"publication_date":"2017-02-01","ids":{"openalex":"https://openalex.org/W2593881748","doi":"https://doi.org/10.1142/s021821301760003x","mag":"2593881748"},"language":"en","primary_location":{"id":"doi:10.1142/s021821301760003x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021821301760003x","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081520679","display_name":"Hadjer Ykhlef","orcid":"https://orcid.org/0000-0002-7791-3321"},"institutions":[{"id":"https://openalex.org/I83332908","display_name":"University of Blida","ror":"https://ror.org/03g41pw14","country_code":"DZ","type":"education","lineage":["https://openalex.org/I83332908"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Hadjer Ykhlef","raw_affiliation_strings":["Department of Computer Science, University of Blida, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Blida, Algeria","institution_ids":["https://openalex.org/I83332908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012408243","display_name":"Djamel Bouchaffra","orcid":"https://orcid.org/0000-0002-9850-907X"},"institutions":[{"id":"https://openalex.org/I4210102186","display_name":"Centre de D\u00e9veloppement des Technologies Avanc\u00e9es","ror":"https://ror.org/01ay87255","country_code":"DZ","type":"facility","lineage":["https://openalex.org/I4210102186"]}],"countries":["DZ"],"is_corresponding":false,"raw_author_name":"Djamel Bouchaffra","raw_affiliation_strings":["Division of Design and Implementation of Intelligent Systems Centre de recherche des technologies avanc\u00e9es, Algeria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Design and Implementation of Intelligent Systems Centre de recherche des technologies avanc\u00e9es, Algeria","institution_ids":["https://openalex.org/I4210102186"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2065,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.61767626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"26","issue":"01","first_page":"1760003","last_page":"1760003"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9987999796867371,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9973000288009644,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.851020336151123},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.7064843773841858},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6338253617286682},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5906085968017578},{"id":"https://openalex.org/keywords/cascading-classifiers","display_name":"Cascading classifiers","score":0.5905776619911194},{"id":"https://openalex.org/keywords/shapley-value","display_name":"Shapley value","score":0.5759807229042053},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5619567632675171},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5013828277587891},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4442746639251709},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4434933364391327},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.33958888053894043},{"id":"https://openalex.org/keywords/game-theory","display_name":"Game theory","score":0.22136729955673218},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10032185912132263}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.851020336151123},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.7064843773841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6338253617286682},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5906085968017578},{"id":"https://openalex.org/C40651066","wikidata":"https://www.wikidata.org/wiki/Q5048220","display_name":"Cascading classifiers","level":4,"score":0.5905776619911194},{"id":"https://openalex.org/C199022921","wikidata":"https://www.wikidata.org/wiki/Q240046","display_name":"Shapley value","level":3,"score":0.5759807229042053},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5619567632675171},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5013828277587891},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4442746639251709},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4434933364391327},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.33958888053894043},{"id":"https://openalex.org/C177142836","wikidata":"https://www.wikidata.org/wiki/Q44455","display_name":"Game theory","level":2,"score":0.22136729955673218},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10032185912132263},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s021821301760003x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021821301760003x","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Artificial Intelligence Tools","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1800056794","https://openalex.org/W1968904042","https://openalex.org/W1975794688","https://openalex.org/W1994943112","https://openalex.org/W2025328644","https://openalex.org/W2028794308","https://openalex.org/W2028847614","https://openalex.org/W2046116913","https://openalex.org/W2046602115","https://openalex.org/W2058796521","https://openalex.org/W2062227078","https://openalex.org/W2065165463","https://openalex.org/W2103346566","https://openalex.org/W2105073720","https://openalex.org/W2127082287","https://openalex.org/W2144781678","https://openalex.org/W2293054526","https://openalex.org/W2411932910"],"related_works":["https://openalex.org/W1970518052","https://openalex.org/W1933712933","https://openalex.org/W2886126675","https://openalex.org/W2074872866","https://openalex.org/W3202701980","https://openalex.org/W2003868635","https://openalex.org/W4205754593","https://openalex.org/W4312206019","https://openalex.org/W2548865325","https://openalex.org/W2902615229"],"abstract_inverted_index":{"Ensemble":[0,50],"methodology":[1],"has":[2],"proved":[3],"to":[4,23],"be":[5],"one":[6],"of":[7,15,28,47,60,103,138,178],"the":[8,44,48,71,101,133,136,139,166,173],"strongest":[9],"machine":[10],"learning":[11],"techniques.":[12],"In":[13,74],"spite":[14],"its":[16,117],"huge":[17],"success,":[18],"most":[19],"ensemble":[20,79,168],"methods":[21,175],"tend":[22],"generate":[24],"unnecessarily":[25],"large":[26],"number":[27],"classifiers,":[29],"which":[30],"entails":[31],"an":[32,104],"increase":[33],"in":[34,43,119,176],"memory":[35],"storage,":[36],"computational":[37,184],"cost,":[38],"and":[39,107,135,169,183],"even":[40],"a":[41,58,83,88,121],"reduction":[42],"generalization":[45],"performance":[46,102],"ensemble.":[49,73],"selection":[51,80,150],"addresses":[52],"these":[53,125],"shortcomings":[54],"by":[55],"searching":[56],"for":[57],"fraction":[59],"individual":[61],"classifiers":[62],"that":[63,99,161],"performs":[64,170],"as":[65,82],"good":[66],"as,":[67],"or":[68],"better":[69,171],"than":[70,172],"entire":[72],"this":[75],"paper,":[76],"we":[77,142],"formulate":[78],"problem":[81],"coalitional":[84],"game":[85,92],"played":[86],"on":[87,116,153],"graph.":[89],"The":[90,158],"proposed":[91,140],"aims":[93],"at":[94],"capturing":[95],"two":[96,126],"crucial":[97],"concepts":[98],"affect":[100],"ensemble:":[105],"accuracy":[106],"diversity.":[108],"Most":[109],"importantly,":[110],"it":[111],"ranks":[112],"every":[113],"classifier":[114],"based":[115,152],"contribution":[118],"keeping":[120],"proper":[122],"balance":[123],"between":[124],"notions":[127],"using":[128],"Shapley":[129],"value.":[130],"To":[131],"demonstrate":[132],"validity":[134],"effectiveness":[137],"approach,":[141],"carried":[143],"out":[144],"experimental":[145],"comparisons":[146],"with":[147],"some":[148],"major":[149],"techniques":[151],"35":[154],"UCI":[155],"benchmark":[156],"datasets.":[157],"results":[159],"reveal":[160],"our":[162],"approach":[163],"significantly":[164],"improves":[165],"original":[167],"other":[174],"terms":[177],"classification":[179],"accuracy,":[180],"pruning":[181],"ratio,":[182],"cost.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}