{"id":"https://openalex.org/W4386450702","doi":"https://doi.org/10.1109/ispds58840.2023.10235653","title":"Enterprise Credit Prediction Model Based on SCC-MIC-Boruta Algorithm Feature Selection Algorithm","display_name":"Enterprise Credit Prediction Model Based on SCC-MIC-Boruta Algorithm Feature Selection Algorithm","publication_year":2023,"publication_date":"2023-07-14","ids":{"openalex":"https://openalex.org/W4386450702","doi":"https://doi.org/10.1109/ispds58840.2023.10235653"},"language":"en","primary_location":{"id":"doi:10.1109/ispds58840.2023.10235653","doi":"https://doi.org/10.1109/ispds58840.2023.10235653","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ispds58840.2023.10235653","pdf_url":null,"source":{"id":"https://openalex.org/S7407088239","display_name":"International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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":null,"display_name":"Kang Xu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kang Xu","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103237947","display_name":"Lingnan Xie","orcid":"https://orcid.org/0009-0008-3753-1231","observed_orcids":["https://orcid.org/0009-0008-3753-1231"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lingnan Xie","raw_affiliation_strings":["Bank of Nanjing,Credit Approval Department,Nanjing,China","Credit Approval Department, Bank of Nanjing, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bank of Nanjing,Credit Approval Department,Nanjing,China","institution_ids":[]},{"raw_affiliation_string":"Credit Approval Department, Bank of Nanjing, Nanjing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112117678","display_name":"Xuechun Liang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuechun Liang","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087836916","display_name":"Tengfei Cao","orcid":"https://orcid.org/0000-0002-0051-4146","observed_orcids":["https://orcid.org/0000-0002-0051-4146"]},"institutions":[{"id":"https://openalex.org/I134687103","display_name":"Nanjing Tech University","ror":"https://ror.org/03sd35x91","country_code":"CN","type":"education","lineage":["https://openalex.org/I134687103"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tengfei Cao","raw_affiliation_strings":["College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Electrical Engineering and Control Science, Nanjing Tech University, Nanjing, China","institution_ids":["https://openalex.org/I134687103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011705308","display_name":"Yingjia Chen","orcid":"https://orcid.org/0009-0004-9737-2392","observed_orcids":["https://orcid.org/0009-0004-9737-2392"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yingjia Chen","raw_affiliation_strings":["Changzhou Guanying Elementary School, Changzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changzhou Guanying Elementary School, Changzhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":0.22149123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"589","last_page":"594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9961000084877014,"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":0.9961000084877014,"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":0.0013000000035390258,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/feature-selection","display_name":"feature selection","score":0.9539999961853027},{"id":"https://openalex.org/keywords/spearman-s-rank-correlation","display_name":"Spearman correlation","score":0.9380000233650208},{"id":"https://openalex.org/keywords/maximal-information-coefficient","display_name":"maximal information coefficient","score":0.9559999704360962},{"id":"https://openalex.org/keywords/boruta-algorithm","display_name":"Boruta algorithm","score":0.9490000009536743},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.6539999842643738},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.9559999704360962},{"id":"https://openalex.org/keywords/gradient-boosted-decision-trees","display_name":"gradient boosting decision tree","score":0.9480000138282776},{"id":"https://openalex.org/keywords/decision-tree","display_name":"decision tree","score":0.47699999809265137}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7369530200958252},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6702684164047241},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6618214845657349},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6144947409629822},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5987734794616699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5818148255348206},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5680662393569946},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.565203845500946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.540873646736145},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.5327520370483398},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.44070619344711304},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.434261679649353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3962196409702301},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3589036464691162},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.1109/ispds58840.2023.10235653","doi":"https://doi.org/10.1109/ispds58840.2023.10235653","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ispds58840.2023.10235653","pdf_url":null,"source":{"id":"https://openalex.org/S7407088239","display_name":"International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G8242812449","display_name":null,"funder_award_id":"11801267","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":false,"pdf":false},"content_urls":null,"referenced_works_count":2,"referenced_works":["https://openalex.org/W2165700458","https://openalex.org/W3092092401"],"related_works":["https://openalex.org/W2789893186","https://openalex.org/W2067671487","https://openalex.org/W2079196938","https://openalex.org/W2078684405","https://openalex.org/W4410486281","https://openalex.org/W4410177351","https://openalex.org/W2028504354","https://openalex.org/W4220923808","https://openalex.org/W2537637268","https://openalex.org/W3141979009"],"abstract_inverted_index":{"A":[0],"method":[1,37,113],"combining":[2],"Spearman":[3],"Correlation":[4],"Coefficient":[5,9],"(SCC),":[6],"Maximal":[7],"Information":[8],"(MIC),":[10],"and":[11,47,62,74,126],"Boruta":[12,77],"algorithm":[13],"is":[14,38,55,65,78,96],"proposed":[15],"to":[16,40,57,67,85,98],"address":[17],"the":[18,69,81,87,92,99,107,115,119],"problem":[19],"of":[20,24,32,118],"low":[21],"classification":[22,101,116,121],"accuracy":[23,117],"traditional":[25],"machine":[26],"learning":[27],"algorithms":[28],"when":[29],"processing":[30],"features":[31,73],"enterprise":[33],"credit":[34],"data.":[35],"The":[36],"applied":[39,97],"Decision":[41,50],"Trees,":[42],"Extreme":[43],"Gradient":[44,48],"Boosting":[45,49],"(XGBOOST),":[46],"Tree":[51],"(GBDT).":[52],"Firstly,":[53],"SCC":[54],"used":[56,66],"remove":[58],"highly":[59],"correlated":[60],"features,":[61],"then":[63],"MIC":[64],"find":[68,86],"strongest":[70],"correlation":[71],"between":[72],"labels.":[75],"Next,":[76],"embedded":[79],"in":[80],"Random":[82],"Forest":[83],"model":[84],"optimal":[88,93],"feature":[89,94,108],"subset.":[90],"Finally,":[91],"subset":[95,109],"three":[100,120],"models.":[102],"Experimental":[103],"results":[104],"show":[105],"that":[106],"selected":[110],"by":[111,123],"this":[112],"improves":[114],"models":[122],"1.18%,":[124],"1.18%":[125],"3.53%,":[127],"respectively.":[128]},"counts_by_year":[],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2023-09-06T00:00:00"}