{"id":"https://openalex.org/W3030606345","doi":"https://doi.org/10.3233/ida-194608","title":"An active learning ensemble method for regression tasks","display_name":"An active learning ensemble method for regression tasks","publication_year":2020,"publication_date":"2020-05-21","ids":{"openalex":"https://openalex.org/W3030606345","doi":"https://doi.org/10.3233/ida-194608","mag":"3030606345"},"language":"en","primary_location":{"id":"doi:10.3233/ida-194608","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194608","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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/A5061070955","display_name":"Nikos Fazakis","orcid":"https://orcid.org/0000-0001-7687-2380"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Nikos Fazakis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027660188","display_name":"Georgios Kostopoulos","orcid":"https://orcid.org/0000-0002-7374-0099"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios Kostopoulos","raw_affiliation_strings":["Educational Software Development Laboratory, Department of Mathematics, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Educational Software Development Laboratory, Department of Mathematics, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073119708","display_name":"Stamatis Karlos","orcid":"https://orcid.org/0000-0002-5307-6186"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stamatis Karlos","raw_affiliation_strings":["Department of Mathematics, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066370772","display_name":"Sotiris Kotsiantis","orcid":"https://orcid.org/0000-0002-2247-3082"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Sotiris Kotsiantis","raw_affiliation_strings":["Educational Software Development Laboratory, Department of Mathematics, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Educational Software Development Laboratory, Department of Mathematics, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012058127","display_name":"Kyriakos Sgarbas","orcid":"https://orcid.org/0000-0002-1797-1343"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Kyriakos Sgarbas","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5061070955"],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":0.3911,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.68017435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"24","issue":"3","first_page":"607","last_page":"623"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9950000047683716,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9469000101089478,"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/machine-learning","display_name":"Machine learning","score":0.7219664454460144},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.721729576587677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7064392566680908},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6373885869979858},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6224510073661804},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6099432706832886},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5492057204246521},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5477298498153687},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5056629180908203},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4578595757484436},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.41750943660736084},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1415465772151947},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12327787280082703},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10358494520187378}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7219664454460144},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.721729576587677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7064392566680908},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6373885869979858},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6224510073661804},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6099432706832886},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5492057204246521},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5477298498153687},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5056629180908203},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4578595757484436},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.41750943660736084},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1415465772151947},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12327787280082703},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10358494520187378},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-194608","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194608","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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":36,"referenced_works":["https://openalex.org/W1511720642","https://openalex.org/W1514707997","https://openalex.org/W1531909365","https://openalex.org/W1568139284","https://openalex.org/W1573810412","https://openalex.org/W1985327665","https://openalex.org/W1993615002","https://openalex.org/W2018770010","https://openalex.org/W2076118331","https://openalex.org/W2091755526","https://openalex.org/W2101234009","https://openalex.org/W2115012618","https://openalex.org/W2122284941","https://openalex.org/W2128073546","https://openalex.org/W2137184539","https://openalex.org/W2138101451","https://openalex.org/W2139709458","https://openalex.org/W2156324002","https://openalex.org/W2183542377","https://openalex.org/W2264960680","https://openalex.org/W2341531400","https://openalex.org/W2396264432","https://openalex.org/W2408920689","https://openalex.org/W2520510166","https://openalex.org/W2556726043","https://openalex.org/W2574867284","https://openalex.org/W2619236481","https://openalex.org/W2788739741","https://openalex.org/W2800666469","https://openalex.org/W2808462996","https://openalex.org/W2911964244","https://openalex.org/W3101504385","https://openalex.org/W4206723194","https://openalex.org/W4245608963","https://openalex.org/W4252861488","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W2056314584","https://openalex.org/W1492505081","https://openalex.org/W1586607209","https://openalex.org/W122912556","https://openalex.org/W4312414840","https://openalex.org/W2621411691","https://openalex.org/W2271357838","https://openalex.org/W1986633584","https://openalex.org/W2556866732","https://openalex.org/W2328989934"],"abstract_inverted_index":{"Active":[0],"learning":[1,7,62,84,107,126,165],"is":[2,31,52,73,95],"a":[3,32,97,123,146],"typical":[4],"approach":[5,166],"for":[6,109],"from":[8],"both":[9],"labeled":[10,35],"and":[11,18,59,80],"unlabeled":[12,50,140],"examples":[13],"aiming":[14],"to":[15,120,135],"build":[16],"efficient":[17],"accurate":[19],"predictive":[20],"models":[21],"at":[22,42],"minimum":[23],"expense":[24],"under":[25],"an":[26],"expert\u2019s":[27],"guidance.":[28],"Since":[29],"there":[30,94],"lack":[33],"of":[34,49,57,90,100,105,139,148,154],"data":[36,51],"in":[37,55,75,87],"many":[38],"scientific":[39],"fields":[40],"whilst,":[41],"the":[43,46,88,103,115,130,137,152,155,162,168],"same":[44],"time,":[45],"labeling":[47],"cost":[48],"typically":[53],"high":[54],"terms":[56],"time":[58],"expenditure,":[60],"active":[61,83,106,125,164],"has":[63],"grown":[64],"rapidly":[65],"over":[66,161],"recent":[67],"years":[68],"with":[69],"great":[70],"success.":[71],"This":[72],"reflected":[74],"various":[76],"studies":[77,101],"providing":[78],"insights":[79],"analyzing":[81],"several":[82],"methods,":[85],"especially":[86],"case":[89],"classification":[91],"tasks,":[92],"whereas,":[93],"only":[96],"limited":[98],"number":[99],"concerning":[102],"implementation":[104],"methods":[108],"regression":[110,127],"ones.":[111],"Within":[112],"this":[113],"context,":[114],"present":[116],"paper":[117],"sets":[118],"out":[119],"put":[121],"forward":[122],"pool-based":[124],"algorithm":[128],"employing":[129],"query":[131],"by":[132],"committee":[133],"strategy":[134],"evaluate":[136],"informativeness":[138],"examples.":[141],"The":[142],"experimental":[143],"results":[144],"on":[145],"plethora":[147],"benchmark":[149],"datasets":[150],"demonstrate":[151],"efficiency":[153],"proposed":[156],"method,":[157],"since":[158],"it":[159],"prevails":[160],"baseline":[163],"applying":[167],"random":[169],"sampling":[170],"strategy,":[171],"as":[172,174],"well":[173],"familiar":[175],"supervised":[176],"methods.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
