{"id":"https://openalex.org/W4294560083","doi":"https://doi.org/10.3390/a15050149","title":"Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring","display_name":"Extreme Learning Machine Enhanced Gradient Boosting for Credit Scoring","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4294560083","doi":"https://doi.org/10.3390/a15050149"},"language":"en","primary_location":{"id":"doi:10.3390/a15050149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a15050149","pdf_url":"https://www.mdpi.com/1999-4893/15/5/149/pdf?version=1651046770","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/15/5/149/pdf?version=1651046770","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101889848","display_name":"Yao Zou","orcid":"https://orcid.org/0000-0002-4296-8138"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yao Zou","raw_affiliation_strings":["Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China"],"affiliations":[{"raw_affiliation_string":"Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106446833","display_name":"Changchun Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changchun Gao","raw_affiliation_strings":["Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China"],"affiliations":[{"raw_affiliation_string":"Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101889848"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":3.8058,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.93439581,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"15","issue":"5","first_page":"149","last_page":"149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9890999794006348,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.9455000162124634,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8086236119270325},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7467858791351318},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7157415151596069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6713590621948242},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6530482769012451},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6479828953742981},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5028435587882996},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4675537347793579},{"id":"https://openalex.org/keywords/credit-risk","display_name":"Credit risk","score":0.4661480188369751},{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.4320200979709625},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.42917001247406006},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.39805540442466736},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.24187567830085754},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.08421328663825989}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8086236119270325},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7467858791351318},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157415151596069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6713590621948242},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6530482769012451},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6479828953742981},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5028435587882996},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4675537347793579},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.4661480188369751},{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.4320200979709625},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.42917001247406006},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.39805540442466736},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.24187567830085754},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.08421328663825989}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/a15050149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a15050149","pdf_url":"https://www.mdpi.com/1999-4893/15/5/149/pdf?version=1651046770","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5a961554695542339c4deb4021543aac","is_oa":true,"landing_page_url":"https://doaj.org/article/5a961554695542339c4deb4021543aac","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 15, Iss 5, p 149 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1999-4893/15/5/149/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/a15050149","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms; Volume 15; Issue 5; Pages: 149","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/a15050149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a15050149","pdf_url":"https://www.mdpi.com/1999-4893/15/5/149/pdf?version=1651046770","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3795415306","display_name":null,"funder_award_id":"71874027","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4294560083.pdf","grobid_xml":"https://content.openalex.org/works/W4294560083.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W647100376","https://openalex.org/W973036012","https://openalex.org/W1982644216","https://openalex.org/W1993922907","https://openalex.org/W1994085451","https://openalex.org/W2029765676","https://openalex.org/W2029869759","https://openalex.org/W2032784723","https://openalex.org/W2041101399","https://openalex.org/W2044804342","https://openalex.org/W2052912973","https://openalex.org/W2053529851","https://openalex.org/W2082868806","https://openalex.org/W2111072639","https://openalex.org/W2200000192","https://openalex.org/W2273893358","https://openalex.org/W2296034778","https://openalex.org/W2461391084","https://openalex.org/W2560858617","https://openalex.org/W2562923621","https://openalex.org/W2586297576","https://openalex.org/W2600353413","https://openalex.org/W2761700016","https://openalex.org/W2768348081","https://openalex.org/W2783336591","https://openalex.org/W2789893186","https://openalex.org/W2789901660","https://openalex.org/W2793304295","https://openalex.org/W2805025666","https://openalex.org/W2945007002","https://openalex.org/W2965973429","https://openalex.org/W2970989889","https://openalex.org/W2998458143","https://openalex.org/W3012383881","https://openalex.org/W3033559620","https://openalex.org/W3034751247","https://openalex.org/W3038714839","https://openalex.org/W3048715644","https://openalex.org/W3082225844","https://openalex.org/W3094559308","https://openalex.org/W3114714171","https://openalex.org/W3133255363","https://openalex.org/W3173725123","https://openalex.org/W3187983203","https://openalex.org/W3197496560","https://openalex.org/W3205154884","https://openalex.org/W4226116665","https://openalex.org/W6621252952","https://openalex.org/W6745609711","https://openalex.org/W6783224473","https://openalex.org/W6795664449"],"related_works":["https://openalex.org/W2327035729","https://openalex.org/W2348748958","https://openalex.org/W3039673966","https://openalex.org/W1538046993","https://openalex.org/W2884325279","https://openalex.org/W1570592793","https://openalex.org/W1525436954","https://openalex.org/W1992847598","https://openalex.org/W4296079469","https://openalex.org/W4298012357"],"abstract_inverted_index":{"Credit":[0],"scoring":[1,80,119,196],"is":[2,72,110,173,203],"an":[3],"effective":[4],"tool":[5],"for":[6,67,180],"banks":[7],"and":[8,28,33,55,154,197],"lending":[9],"companies":[10],"to":[11,45,159,175,207],"manage":[12],"the":[13,47,63,82,88,92,103,117,124,129,136,146,149,161,177,200],"potential":[14],"credit":[15,50,69,79,118,181,188,195,210],"risk":[16],"of":[17,31,42,49,106,138,148,163],"borrowers.":[18,35],"Machine":[19],"learning":[20,168],"algorithms":[21],"have":[22,61],"made":[23],"grand":[24],"progress":[25],"in":[26,194],"automatic":[27],"accurate":[29,78,209],"discrimination":[30],"good":[32,205],"bad":[34],"Notably,":[36],"ensemble":[37,65,75,113,151,156],"approaches":[38],"are":[39],"a":[40,73,111,191,204],"group":[41],"powerful":[43],"tools":[44],"enhance":[46,160,176],"performance":[48],"scoring.":[51,70,182,211],"Random":[52],"forest":[53],"(RF)":[54],"Gradient":[56],"Boosting":[57],"Decision":[58],"Tree":[59],"(GBDT)":[60],"become":[62],"mainstream":[64],"methods":[66],"precise":[68],"RF":[71],"Bagging-based":[74],"that":[76,95,115,199],"realizes":[77],"enriches":[81],"diversity":[83,137,162],"base":[84,107,139,164],"learners":[85],"by":[86,121],"modifying":[87],"training":[89,99,125,130,152],"object.":[90],"However,":[91],"optimization":[93,157],"pattern":[94,158],"works":[96],"on":[97,185],"invariant":[98],"targets":[100],"may":[101,134],"increase":[102],"statistical":[104],"independence":[105],"learners.":[108,140,165],"GBDT":[109,172],"boosting-based":[112],"approach":[114],"reduces":[116],"error":[120],"iteratively":[122],"changing":[123],"target":[126],"while":[127],"keeping":[128],"features":[131],"unchanged.":[132],"This":[133],"harm":[135],"In":[141],"this":[142],"study,":[143],"we":[144],"incorporate":[145],"advantages":[147],"Bagging":[150],"strategy":[153],"boosting":[155],"An":[166],"extreme":[167],"machine-based":[169],"supervised":[170],"augmented":[171],"proposed":[174,201],"discriminative":[178],"ability":[179],"Experimental":[183],"results":[184],"4":[186],"public":[187],"datasets":[189],"show":[190],"significant":[192],"improvement":[193],"suggest":[198],"method":[202],"solution":[206],"realize":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2022-09-04T00:00:00"}