{"id":"https://openalex.org/W2057521255","doi":"https://doi.org/10.1007/s10618-014-0383-9","title":"Ensemble methods for uplift modeling","display_name":"Ensemble methods for uplift modeling","publication_year":2014,"publication_date":"2014-09-17","ids":{"openalex":"https://openalex.org/W2057521255","doi":"https://doi.org/10.1007/s10618-014-0383-9","mag":"2057521255"},"language":"en","primary_location":{"id":"doi:10.1007/s10618-014-0383-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-014-0383-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-014-0383-9.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10618-014-0383-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025672533","display_name":"Micha\u0142 So\u0142tys","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]},{"id":"https://openalex.org/I99542240","display_name":"Polish Academy of Sciences","ror":"https://ror.org/01dr6c206","country_code":"PL","type":"funder","lineage":["https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Micha\u0142 So\u0142tys","raw_affiliation_strings":["Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland","institution_ids":["https://openalex.org/I99542240","https://openalex.org/I4210087266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068666126","display_name":"Szymon Jaroszewicz","orcid":"https://orcid.org/0000-0001-9327-5019"},"institutions":[{"id":"https://openalex.org/I4210125529","display_name":"National Institute of Telecommunications","ror":"https://ror.org/03053v606","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210125529"]},{"id":"https://openalex.org/I99542240","display_name":"Polish Academy of Sciences","ror":"https://ror.org/01dr6c206","country_code":"PL","type":"funder","lineage":["https://openalex.org/I99542240"]},{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Szymon Jaroszewicz","raw_affiliation_strings":["Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland","National Institute of Telecommunications, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland","institution_ids":["https://openalex.org/I99542240","https://openalex.org/I4210087266"]},{"raw_affiliation_string":"National Institute of Telecommunications, Warsaw, Poland","institution_ids":["https://openalex.org/I4210125529"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060872417","display_name":"Piotr Rzepakowski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210125529","display_name":"National Institute of Telecommunications","ror":"https://ror.org/03053v606","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210125529"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Piotr Rzepakowski","raw_affiliation_strings":["National Institute of Telecommunications, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Telecommunications, Warsaw, Poland","institution_ids":["https://openalex.org/I4210125529"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025672533"],"corresponding_institution_ids":["https://openalex.org/I4210087266","https://openalex.org/I99542240"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":4.366,"has_fulltext":true,"cited_by_count":79,"citation_normalized_percentile":{"value":0.94660451,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"29","issue":"6","first_page":"1531","last_page":"1559"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9937000274658203,"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/T10136","display_name":"Statistical Methods and Inference","score":0.9887999892234802,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.8096679449081421},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7630215883255005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7089347243309021},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6701183319091797},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6086142659187317},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6075115203857422},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5557698011398315},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5129439234733582},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4875602126121521},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4683847725391388},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.4609639346599579},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3365946412086487}],"concepts":[{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.8096679449081421},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7630215883255005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7089347243309021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6701183319091797},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6086142659187317},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6075115203857422},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5557698011398315},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5129439234733582},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4875602126121521},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4683847725391388},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.4609639346599579},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3365946412086487},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10618-014-0383-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-014-0383-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-014-0383-9.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10618-014-0383-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10618-014-0383-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10618-014-0383-9.pdf","source":{"id":"https://openalex.org/S121920818","display_name":"Data Mining and Knowledge Discovery","issn_l":"1384-5810","issn":["1384-5810","1573-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Mining and Knowledge Discovery","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G3637203501","display_name":null,"funder_award_id":"N N516 414938","funder_id":"https://openalex.org/F4320322733","funder_display_name":"Ministerstwo Edukacji i Nauki"}],"funders":[{"id":"https://openalex.org/F4320322733","display_name":"Ministerstwo Edukacji i Nauki","ror":"https://ror.org/05dwvd537"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2057521255.pdf","grobid_xml":"https://content.openalex.org/works/W2057521255.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W179935622","https://openalex.org/W187340461","https://openalex.org/W1531283906","https://openalex.org/W1534477342","https://openalex.org/W1549565124","https://openalex.org/W1565746575","https://openalex.org/W1570448133","https://openalex.org/W1594031697","https://openalex.org/W1599871777","https://openalex.org/W1603952207","https://openalex.org/W1976459656","https://openalex.org/W1978108654","https://openalex.org/W1981886486","https://openalex.org/W1988790447","https://openalex.org/W2011485768","https://openalex.org/W2043915660","https://openalex.org/W2055309977","https://openalex.org/W2056132907","https://openalex.org/W2072837080","https://openalex.org/W2085227190","https://openalex.org/W2100600375","https://openalex.org/W2110228583","https://openalex.org/W2116742087","https://openalex.org/W2125055259","https://openalex.org/W2134696506","https://openalex.org/W2135293965","https://openalex.org/W2135406060","https://openalex.org/W2136185850","https://openalex.org/W2140899775","https://openalex.org/W2167816518","https://openalex.org/W2591957553","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2966207845","https://openalex.org/W3085162807","https://openalex.org/W3124500396","https://openalex.org/W4210325252","https://openalex.org/W4239587501","https://openalex.org/W4293404332"],"related_works":["https://openalex.org/W2944292463","https://openalex.org/W3014252901","https://openalex.org/W2188759683","https://openalex.org/W2794896638","https://openalex.org/W4317376680","https://openalex.org/W4360777922","https://openalex.org/W1807784185","https://openalex.org/W3208169454","https://openalex.org/W4390905871","https://openalex.org/W3202800081"],"abstract_inverted_index":{"Uplift":[0],"modeling":[1,175,208],"is":[2,147],"a":[3,20,24,28,37,47,52,138,148,192],"branch":[4],"of":[5,15,77,98,129,140,150,173,188],"machine":[6],"learning":[7],"which":[8,144,176],"aims":[9],"at":[10],"predicting":[11],"the":[12,44,66,75,96,151,157,167,186,206],"causal":[13],"effect":[14],"an":[16,89],"action":[17,67],"such":[18],"as":[19,51,202],"marketing":[21],"campaign":[22],"or":[23],"medical":[25],"treatment":[26,38,158],"on":[27],"given":[29],"individual":[30],"by":[31],"taking":[32],"into":[33,114],"account":[34],"responses":[35],"in":[36,84,103,106,127,145,156,205],"group,":[39],"containing":[40],"individuals":[41,63],"subject":[42],"to":[43,61,93,164,185],"action,":[45],"and":[46,81,159,195],"control":[48,160],"group":[49],"serving":[50],"background.":[53],"The":[54,119,171],"resulting":[55],"model":[56,107,165],"can":[57],"then":[58],"be":[59,69],"used":[60],"select":[62],"for":[64],"whom":[65],"will":[68],"most":[70],"profitable.":[71],"This":[72],"paper":[73],"analyzes":[74],"use":[76],"ensemble":[78,142,189],"methods:":[79],"bagging":[80,194],"random":[82,196],"forests":[83,197],"uplift":[85,117,174,207],"modeling.":[86],"We":[87,132],"perform":[88],"extensive":[90],"experimental":[91],"evaluation":[92,201],"demonstrate":[94],"that":[95,134],"application":[97,187],"those":[99,125,135],"methods":[100],"often":[101],"results":[102],"spectacular":[104],"gains":[105,120,136],"performance,":[108],"turning":[109],"almost":[110],"useless":[111],"single":[112],"models":[113],"highly":[115],"capable":[116],"ensembles.":[118],"are":[121,137],"much":[122],"larger":[123],"than":[124,166],"achieved":[126],"case":[128],"standard":[130],"classification.":[131],"show":[133],"result":[139,149],"high":[141],"diversity,":[143],"turn":[146],"differences":[152],"between":[153],"class":[154,168],"probabilities":[155,169],"groups":[161],"being":[162],"harder":[163],"themselves.":[170],"feature":[172],"makes":[177,182],"it":[178,183],"difficult":[179],"thus":[180],"also":[181],"amenable":[184],"methods.":[190],"As":[191],"result,":[193],"emerge":[198],"from":[199],"our":[200],"key":[203],"tools":[204],"toolbox.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":2}],"updated_date":"2026-05-13T08:25:38.343686","created_date":"2025-10-10T00:00:00"}