{"id":"https://openalex.org/W4308335032","doi":"https://doi.org/10.3233/ida-216228","title":"Credit scoring based on a Bagging-cascading boosted decision tree","display_name":"Credit scoring based on a Bagging-cascading boosted decision tree","publication_year":2022,"publication_date":"2022-11-04","ids":{"openalex":"https://openalex.org/W4308335032","doi":"https://doi.org/10.3233/ida-216228"},"language":"en","primary_location":{"id":"doi:10.3233/ida-216228","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-216228","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/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":false,"raw_author_name":"Yao Zou","raw_affiliation_strings":["Glorious Sun School of Business and Management, Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Glorious Sun School of Business and Management, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","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, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Glorious Sun School of Business and Management, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047110623","display_name":"Meng Xia","orcid":"https://orcid.org/0000-0003-0598-0485"},"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":"Meng Xia","raw_affiliation_strings":["College of Information Science and Technology, Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068288622","display_name":"Congyuan Pang","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":"Congyuan Pang","raw_affiliation_strings":["Glorious Sun School of Business and Management, Donghua University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Glorious Sun School of Business and Management, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20023868,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"26","issue":"6","first_page":"1557","last_page":"1578"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"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":0.9998000264167786,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9929999709129333,"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/T11496","display_name":"Credit Risk and Financial Regulations","score":0.9394999742507935,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.8929212093353271},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.744584858417511},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7131193280220032},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6709721684455872},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6331043839454651},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6274245381355286},{"id":"https://openalex.org/keywords/bootstrap-aggregating","display_name":"Bootstrap aggregating","score":0.5915635824203491},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.5853949189186096},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5624569654464722},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5365502834320068},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.47199419140815735},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.360960990190506}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8929212093353271},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.744584858417511},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7131193280220032},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6709721684455872},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6331043839454651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6274245381355286},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.5915635824203491},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.5853949189186096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5624569654464722},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5365502834320068},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.47199419140815735},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.360960990190506},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-216228","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-216228","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W973036012","https://openalex.org/W1973982793","https://openalex.org/W1982644216","https://openalex.org/W2004076523","https://openalex.org/W2029765676","https://openalex.org/W2041101399","https://openalex.org/W2044804342","https://openalex.org/W2053529851","https://openalex.org/W2056221673","https://openalex.org/W2082868806","https://openalex.org/W2106612916","https://openalex.org/W2131816657","https://openalex.org/W2133064331","https://openalex.org/W2273893358","https://openalex.org/W2278519563","https://openalex.org/W2278756223","https://openalex.org/W2560858617","https://openalex.org/W2562923621","https://openalex.org/W2586297576","https://openalex.org/W2614275469","https://openalex.org/W2761700016","https://openalex.org/W2765458100","https://openalex.org/W2783336591","https://openalex.org/W2805025666","https://openalex.org/W2806286552","https://openalex.org/W2888997571","https://openalex.org/W2891295587","https://openalex.org/W2895269073","https://openalex.org/W2904485001","https://openalex.org/W2908640594","https://openalex.org/W2943857514","https://openalex.org/W2951781852","https://openalex.org/W2965973429","https://openalex.org/W2970989889","https://openalex.org/W2974656316","https://openalex.org/W2980493715","https://openalex.org/W2989288602","https://openalex.org/W3009609110","https://openalex.org/W3013460382","https://openalex.org/W3017645055","https://openalex.org/W3033559620","https://openalex.org/W3048715644","https://openalex.org/W3091695621","https://openalex.org/W3093314742","https://openalex.org/W3094559308","https://openalex.org/W3138239626","https://openalex.org/W3187983203","https://openalex.org/W3205154884","https://openalex.org/W4226116665","https://openalex.org/W6766321430","https://openalex.org/W6798936786"],"related_works":["https://openalex.org/W3036530763","https://openalex.org/W3100297620","https://openalex.org/W4298012357","https://openalex.org/W4296901315","https://openalex.org/W4285298015","https://openalex.org/W4293069612","https://openalex.org/W3124733172","https://openalex.org/W1978163942","https://openalex.org/W4375930479","https://openalex.org/W46572615"],"abstract_inverted_index":{"Establishing":[0],"precise":[1],"credit":[2,14,33,41,156,179],"scoring":[3,42,180],"models":[4],"to":[5,114,119,148],"predict":[6],"the":[7,29,40,46,54,59,73,76,89,105,109,116,123,127,139,150,161,169],"potential":[8],"default":[9],"probability":[10],"is":[11,112,131],"vital":[12],"for":[13,155],"risk":[15],"management.":[16],"Machine":[17],"learning":[18,22],"models,":[19],"especially":[20],"ensemble":[21,37,51,69,78,82,129,143],"approaches,":[23],"have":[24],"shown":[25],"substantial":[26],"progress":[27],"in":[28,122,134],"performance":[30,43],"improvement":[31],"of":[32,75,91,152],"scoring.":[34,157],"The":[35,94],"Bagging":[36,77,110],"approach":[38],"improves":[39],"by":[44,57],"optimizing":[45],"prediction":[47,55,60],"variance":[48,153],"while":[49],"boosting":[50,81],"algorithms":[52],"reduce":[53],"error":[56],"controlling":[58],"bias.":[61],"In":[62],"this":[63],"study,":[64],"we":[65],"propose":[66],"a":[67,100,135,145,176],"hybrid":[68,142],"method":[70,96],"that":[71],"combines":[72],"advantages":[74],"strategy":[79,111],"and":[80,165],"optimization":[83],"pattern,":[84],"which":[85,103],"can":[86],"well":[87],"balance":[88,149],"tradeoff":[90,151],"variance-bias":[92],"optimization.":[93],"proposed":[95,124,140,170],"considers":[97],"XGBoost":[98],"as":[99],"base":[101,117],"learner,":[102],"ensures":[104],"low-bias":[106],"prediction.":[107],"Moreover,":[108],"introduced":[113],"train":[115],"learner":[118],"prevent":[120],"over-fitting":[121],"method.":[125],"Besides,":[126],"Bagging-boosting":[128],"algorithm":[130,144],"further":[132],"assembled":[133],"cascading":[136],"way,":[137],"making":[138],"new":[141],"good":[146],"solution":[147],"bias":[154],"Experimental":[158],"results":[159],"on":[160],"Australian,":[162],"German,":[163],"Japanese,":[164],"Taiwan":[166],"datasets":[167],"show":[168],"Bagging-cascading":[171],"boosted":[172],"decision":[173],"tree":[174],"provides":[175],"more":[177],"accurate":[178],"result.":[181]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
