{"id":"https://openalex.org/W2763428025","doi":"https://doi.org/10.1109/cscwd.2017.8066746","title":"Credit scoring using ensemble classification based on variable weighting clustering","display_name":"Credit scoring using ensemble classification based on variable weighting clustering","publication_year":2017,"publication_date":"2017-04-01","ids":{"openalex":"https://openalex.org/W2763428025","doi":"https://doi.org/10.1109/cscwd.2017.8066746","mag":"2763428025"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd.2017.8066746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd.2017.8066746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101721084","display_name":"Haiyang Ding","orcid":"https://orcid.org/0000-0003-1522-5627"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyang Ding","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364191","display_name":"Peng Zhang","orcid":"https://orcid.org/0000-0002-9109-4625"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Zhang","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004237040","display_name":"Tun Lu","orcid":"https://orcid.org/0000-0002-6633-4826"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tun Lu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071156485","display_name":"Hansu Gu","orcid":"https://orcid.org/0000-0002-1426-3210"},"institutions":[{"id":"https://openalex.org/I131787340","display_name":"Seagate (United States)","ror":"https://ror.org/04p1xtv71","country_code":"US","type":"company","lineage":["https://openalex.org/I131787340"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hansu Gu","raw_affiliation_strings":["Seagate Technology, Longmont, Colorado, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seagate Technology, Longmont, Colorado, USA","institution_ids":["https://openalex.org/I131787340"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091087409","display_name":"Ning Gu","orcid":"https://orcid.org/0000-0002-2915-974X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Gu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"509","last_page":"514"},"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":0.9983999729156494,"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/T11995","display_name":"FinTech, Crowdfunding, Digital Finance","score":0.9307000041007996,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7716752290725708},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7511129379272461},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7313625812530518},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5974211692810059},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5909659266471863},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.569026529788971},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.5193296670913696},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5185452103614807},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.500960111618042},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4866507947444916},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3735809922218323},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1519116461277008}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7716752290725708},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7511129379272461},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7313625812530518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5974211692810059},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5909659266471863},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.569026529788971},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5193296670913696},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5185452103614807},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.500960111618042},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4866507947444916},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3735809922218323},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1519116461277008},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd.2017.8066746","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cscwd.2017.8066746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1536796998","https://openalex.org/W1966528570","https://openalex.org/W1973445272","https://openalex.org/W1982120517","https://openalex.org/W1988790447","https://openalex.org/W2004076523","https://openalex.org/W2005510983","https://openalex.org/W2024124554","https://openalex.org/W2051455168","https://openalex.org/W2088048599","https://openalex.org/W2089933214","https://openalex.org/W2101234009","https://openalex.org/W2103780778","https://openalex.org/W2131816657","https://openalex.org/W2153427953","https://openalex.org/W2164636120","https://openalex.org/W2278519563","https://openalex.org/W2370035765","https://openalex.org/W2402832337","https://openalex.org/W2517845378","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W3120740533","https://openalex.org/W4248437541","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W1981866886","https://openalex.org/W1964832275","https://openalex.org/W2389865566","https://openalex.org/W2052615004","https://openalex.org/W2407804800","https://openalex.org/W2388864896","https://openalex.org/W2888937984","https://openalex.org/W2031651184","https://openalex.org/W2031173026","https://openalex.org/W2117265009"],"abstract_inverted_index":{"Credit":[0],"scoring":[1,32],"plays":[2],"an":[3],"important":[4],"role":[5],"in":[6,127,154,184,200],"financial":[7],"institutions":[8],"and":[9,51,75,105,188],"debt":[10],"based":[11,59,139],"crowdfunding":[12],"platforms":[13],"as":[14,16],"well":[15],"peer":[17,19],"to":[18,64,120,164,174,194],"lending":[20],"platforms.":[21],"In":[22,161],"the":[23,39,48,52,66,88,97,103,106,115,121,134,147,155,166,179,185,201,212,215],"last":[24],"few":[25],"years,":[26],"adopting":[27],"ensemble":[28,42,137,159,216],"methods":[29,43],"for":[30,80],"credit":[31],"has":[33],"become":[34],"much":[35],"more":[36],"popular.":[37],"However,":[38,114],"performance":[40,135,148,157,213],"of":[41,54,69,100,108,118,136,149,158,214],"is":[44,62],"easily":[45],"affected":[46],"by":[47,73,83,92],"parameter":[49,78],"settings":[50,79],"number":[53,68,107],"base":[55,70,81,109,150],"classifiers.":[56,160],"Ensemble":[57],"classification":[58],"on":[60,87,140],"clustering":[61,74,129,186],"able":[63],"determine":[65],"best":[67],"classifiers":[71,82,110,138],"automatically":[72],"find":[76],"optimal":[77],"training":[84,89,144,198,202],"them":[85],"individually":[86],"subsets":[90,145,199],"combined":[91],"clusters.":[93],"By":[94],"this":[95],"way,":[96],"adverse":[98],"effect":[99],"manually":[101],"setting":[102],"parameters":[104],"can":[111,210],"be":[112],"avoided.":[113],"different":[116,172,175],"contributions":[117],"attributes":[119],"distance":[122,180],"metrics":[123],"are":[124],"not":[125],"considered":[126],"conventional":[128],"methods,":[130],"which":[131,152],"may":[132],"decrease":[133,146],"them.":[141],"Moreover,":[142],"unbalanced":[143,197],"classifiers,":[151],"results":[153,205],"bad":[156],"our":[162,208],"approach,":[163],"address":[165],"above":[167],"problems,":[168],"we":[169],"first":[170],"assign":[171],"weights":[173],"variables":[176],"when":[177],"measuring":[178],"between":[181],"two":[182],"instances":[183],"step,":[187],"then":[189],"adopt":[190],"Subagging":[191],"resampling":[192],"method":[193],"deal":[195],"with":[196],"process.":[203],"Experimental":[204],"show":[206],"that":[207],"approach":[209],"improve":[211],"classifier.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}