{"id":"https://openalex.org/W4308008776","doi":"https://doi.org/10.3233/jifs-221652","title":"A novel SSA-CatBoost machine learning model for credit rating","display_name":"A novel SSA-CatBoost machine learning model for credit rating","publication_year":2022,"publication_date":"2022-10-31","ids":{"openalex":"https://openalex.org/W4308008776","doi":"https://doi.org/10.3233/jifs-221652"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-221652","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-221652","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":"Journal of Intelligent &amp; Fuzzy Systems","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/A5059294968","display_name":"Yang Rui-cheng","orcid":"https://orcid.org/0000-0003-4992-5509"},"institutions":[{"id":"https://openalex.org/I228616957","display_name":"Inner Mongolia University of Finance and Economics","ror":"https://ror.org/02311bm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I228616957"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruicheng Yang","raw_affiliation_strings":["Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China","institution_ids":["https://openalex.org/I228616957"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009398998","display_name":"Pucong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I228616957","display_name":"Inner Mongolia University of Finance and Economics","ror":"https://ror.org/02311bm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I228616957"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pucong Wang","raw_affiliation_strings":["Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China","institution_ids":["https://openalex.org/I228616957"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101423798","display_name":"Ji Qi","orcid":"https://orcid.org/0009-0002-8829-309X"},"institutions":[{"id":"https://openalex.org/I228616957","display_name":"Inner Mongolia University of Finance and Economics","ror":"https://ror.org/02311bm93","country_code":"CN","type":"education","lineage":["https://openalex.org/I228616957"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Qi","raw_affiliation_strings":["Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Finance School, Inner Mongolia University of Finance and Economics, Hohhot, Inner Mongolia, China","institution_ids":["https://openalex.org/I228616957"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059294968"],"corresponding_institution_ids":["https://openalex.org/I228616957"],"apc_list":null,"apc_paid":null,"fwci":5.1447,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.95651454,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"44","issue":"2","first_page":"2269","last_page":"2284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9973999857902527,"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":0.9973999857902527,"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":0.9787999987602234,"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/T11122","display_name":"Online Learning and Analytics","score":0.9455000162124634,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7110581994056702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7051975131034851},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.6385839581489563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6337611675262451},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5901433825492859},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5081965923309326},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41170990467071533},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34581777453422546}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7110581994056702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051975131034851},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.6385839581489563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6337611675262451},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5901433825492859},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5081965923309326},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41170990467071533},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34581777453422546},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-221652","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-221652","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":"Journal of Intelligent &amp; Fuzzy Systems","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":25,"referenced_works":["https://openalex.org/W1965887948","https://openalex.org/W1988610730","https://openalex.org/W2090727353","https://openalex.org/W2590739781","https://openalex.org/W2780157115","https://openalex.org/W2943743498","https://openalex.org/W2955070195","https://openalex.org/W2958680336","https://openalex.org/W2995012791","https://openalex.org/W2998553334","https://openalex.org/W3004933906","https://openalex.org/W3015850483","https://openalex.org/W3022030506","https://openalex.org/W3033067191","https://openalex.org/W3075354065","https://openalex.org/W3081743379","https://openalex.org/W3094948551","https://openalex.org/W3102857415","https://openalex.org/W3109254873","https://openalex.org/W3109641554","https://openalex.org/W3112614053","https://openalex.org/W3125514172","https://openalex.org/W3126720980","https://openalex.org/W3128020858","https://openalex.org/W3169196869"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2133382151","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"Categorical":[0],"Boost":[1],"(CatBoost)":[2],"is":[3,107,149],"a":[4,39,98,160],"new":[5],"approach":[6],"in":[7,179],"credit":[8,58,184],"rating.":[9,59],"In":[10,60,93],"the":[11,30,65,69,77,82,87,111,118,127,130,141,145,153,156,167,172,188,192],"process":[12],"of":[13,33,62,89,95,114,129],"classification":[14,31,53,90,180],"and":[15,21,49,54,75,80,91,120,181,195],"prediction":[16,55,142,182],"using":[17],"CatBoost,":[18],"parameter":[19,63,84],"tuning":[20],"feature":[22,96],"selection":[23],"are":[24,137],"two":[25],"crucial":[26],"parts,":[27],"which":[28,43],"affect":[29],"accuracy":[32,56,88,178],"CatBoost":[34,50,193],"significantly.":[35],"This":[36],"paper":[37],"proposes":[38],"novel":[40,99],"SSA-CatBoost":[41,66,132,173,189],"model,":[42,133],"mixes":[44],"Sparrow":[45],"Search":[46],"Algorithm":[47],"(SSA)":[48],"to":[51,85,109,139,151],"improve":[52,86],"for":[57,183],"terms":[61,94],"tuning,":[64],"optimization":[67],"obtains":[68],"most":[70],"optimal":[71,83],"parameters":[72],"by":[73,186],"iterating":[74],"updating":[76],"sparrow\u2019s":[78],"position,":[79],"utilize":[81],"prediction.":[92],"selection,":[97],"wrapping":[100],"method":[101],"called":[102],"Recursive":[103],"Feature":[104],"Elimination":[105],"algorithm":[106],"adopted":[108],"reduce":[110],"adverse":[112],"impact":[113],"noise":[115],"data":[116],"on":[117],"results,":[119,143],"further":[121],"improves":[122],"calculation":[123],"efficiency.":[124],"To":[125],"evaluate":[126],"performance":[128],"proposed":[131,157],"P2P":[134],"lending":[135],"datasets":[136],"employed":[138],"assess":[140],"then":[144],"interpretable":[146],"Shap":[147],"package":[148],"used":[150],"explain":[152],"reason":[154],"why":[155],"model":[158,174,190,194],"considers":[159],"sample":[161],"as":[162],"good":[163],"or":[164],"bad.":[165],"Consequently,":[166],"experimental":[168],"results":[169],"show":[170],"that":[171],"has":[175],"an":[176],"ideal":[177],"rating":[185],"comparing":[187],"with":[191],"other":[196],"well-known":[197],"machine":[198],"learning":[199],"models.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
