{"id":"https://openalex.org/W2789893186","doi":"https://doi.org/10.1109/ccwc.2018.8301707","title":"A novel credit scoring model based on optimized random forest","display_name":"A novel credit scoring model based on optimized random forest","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2789893186","doi":"https://doi.org/10.1109/ccwc.2018.8301707","mag":"2789893186"},"language":"en","primary_location":{"id":"doi:10.1109/ccwc.2018.8301707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc.2018.8301707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC)","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/A5020185891","display_name":"Xingzhi Zhang","orcid":"https://orcid.org/0000-0002-2098-2246"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingzhi Zhang","raw_affiliation_strings":["SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100318838","display_name":"Yang Yan","orcid":"https://orcid.org/0000-0002-0510-0997"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yang","raw_affiliation_strings":["SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063427973","display_name":"Zhurong Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhurong Zhou","raw_affiliation_strings":["SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SOUTHWEST UNIVERSITY, COLLEGE OF COMPUTER & INFORMATION SCIENCE, Chongqing, CHINA","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":22.4921,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.99452055,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"60","last_page":"65"},"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":0.9843999743461609,"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":0.930899977684021,"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/support-vector-machine","display_name":"Support vector machine","score":0.7197604179382324},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7134610414505005},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6970064640045166},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6537918448448181},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6245283484458923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6188926696777344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.465432345867157},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41543883085250854},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41499030590057373}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7197604179382324},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134610414505005},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6970064640045166},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6537918448448181},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6245283484458923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6188926696777344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.465432345867157},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41543883085250854},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41499030590057373},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccwc.2018.8301707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccwc.2018.8301707","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1963607983","https://openalex.org/W1977009091","https://openalex.org/W1998492739","https://openalex.org/W2029869759","https://openalex.org/W2029981389","https://openalex.org/W2056221673","https://openalex.org/W2070236178","https://openalex.org/W2077625710","https://openalex.org/W2079196938","https://openalex.org/W2083352970","https://openalex.org/W2083964139","https://openalex.org/W2090687467","https://openalex.org/W2103780778","https://openalex.org/W2149851883","https://openalex.org/W2336505047","https://openalex.org/W2415158095","https://openalex.org/W2973651390","https://openalex.org/W3120740533"],"related_works":["https://openalex.org/W4396689146","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W2004826645","https://openalex.org/W4388745254","https://openalex.org/W2980082554","https://openalex.org/W1517228774","https://openalex.org/W2767419625","https://openalex.org/W2389704471","https://openalex.org/W4386564352"],"abstract_inverted_index":{"With":[0],"the":[1,5,18,64,78,120,123,131,137,143,147,164,167,178,190],"rapid":[2],"development":[3],"of":[4,58,80,84,122,166],"credit":[6,8,19,22,48,65,85,100,151],"industry,":[7],"scoring":[9,23,49,101],"models":[10,24],"has":[11,184],"become":[12],"a":[13,55,81,98,185],"very":[14],"important":[15],"issue":[16],"in":[17,52,63,154,188],"industry.":[20],"Many":[21],"based":[25,105],"on":[26,106],"machine":[27,43],"learning":[28],"have":[29],"been":[30],"widely":[31],"used.":[32],"Such":[33],"as":[34,142,159],"artificial":[35],"neural":[36],"network":[37],"(ANN),":[38],"rough":[39],"set,":[40],"support":[41],"vector":[42],"(SVM),":[44],"and":[45,60,73,109,125,128],"other":[46],"innovative":[47],"models.":[50],"However,":[51],"practical":[53],"applications,":[54],"large":[56,82],"amount":[57],"irrelevant":[59,124],"redundant":[61,126],"features":[62,127],"data,":[66,86],"which":[67],"leads":[68],"to":[69,112,129,145,162],"higher":[70,132],"computational":[71],"complexity":[72],"lower":[74],"prediction":[75,133,191],"accuracy.":[76,134,192],"So,":[77],"face":[79],"number":[83],"effective":[87],"feature":[88,107],"selection":[89,108],"method":[90],"is":[91,140],"necessary.":[92],"In":[93,135],"this":[94],"paper,":[95],"we":[96],"propose":[97],"novel":[99],"model,":[102],"called":[103],"NCSM,":[104,136],"grid":[110],"search":[111],"optimize":[113],"random":[114],"forest":[115],"algorithm.":[116],"The":[117],"model":[118],"reduces":[119],"influence":[121],"get":[130],"information":[138],"entropy":[139],"regarded":[141],"heuristic":[144],"select":[146],"optimal":[148],"feature.":[149],"Two":[150],"data":[152,161],"sets":[153],"UCI":[155],"database":[156],"are":[157],"used":[158],"experimental":[160,179],"demonstrate":[163],"accuracy":[165],"NCSM.":[168],"Compared":[169],"with":[170],"linear":[171],"SVM,":[172],"CART,":[173],"MLP,":[174],"H2O":[175],"RF":[176],"models,":[177],"result":[180],"shows":[181],"that":[182],"NCSM":[183],"superior":[186],"performance":[187],"improving":[189]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
