The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data.
<p>The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data.</p>
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2025
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| _version_ | 1852019995167424512 |
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| author | Yetong Fang (21433414) |
| author_facet | Yetong Fang (21433414) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yetong Fang (21433414) |
| dc.date.none.fl_str_mv | 2025-05-27T18:00:46Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0322225.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/The_Model_efficiency_verification_and_comparison_result_on_Taiwan_Credit_Default_Data_and_Home_Credit_Default_Risk_Data_/29159122 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Ecology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified lendingclub loan dataset integrating advanced technologies innovative technical solution handling time dependencies grey wolf optimization experimental results show effectively capture patterns customer historical behaviors 65 %, rmse 0 %, 21 traditional method plawiak paper performs well optimizing key parameters dimensional financial data credit score prediction cnn performs well 51 %, 4 5 %, 68 limited prediction performance gwo model proposed 4 %, traditional methods paper proposes overall performance key component gwo algorithm financial industry financial field xlink "> significantly improving risk management hyperparameter tuning generalization ability fully capturing feature extraction existing methods digital transformation deep learning combines cnns |
| dc.title.none.fl_str_mv | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <p>The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_5cc3bb0f6fd41b2f08e0c717cf98abbd |
| identifier_str_mv | 10.1371/journal.pone.0322225.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29159122 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data.Yetong Fang (21433414)EcologyScience PolicyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedlendingclub loan datasetintegrating advanced technologiesinnovative technical solutionhandling time dependenciesgrey wolf optimizationexperimental results showeffectively capture patternscustomer historical behaviors65 %, rmse0 %, 21traditional method plawiakpaper performs welloptimizing key parametersdimensional financial datacredit score predictioncnn performs well51 %, 45 %, 68limited prediction performancegwo model proposed4 %,traditional methodspaper proposesoverall performancekey componentgwo algorithmfinancial industryfinancial fieldxlink ">significantly improvingrisk managementhyperparameter tuninggeneralization abilityfully capturingfeature extractionexisting methodsdigital transformationdeep learningcombines cnns<p>The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data.</p>2025-05-27T18:00:46ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0322225.t004https://figshare.com/articles/dataset/The_Model_efficiency_verification_and_comparison_result_on_Taiwan_Credit_Default_Data_and_Home_Credit_Default_Risk_Data_/29159122CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/291591222025-05-27T18:00:46Z |
| spellingShingle | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. Yetong Fang (21433414) Ecology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified lendingclub loan dataset integrating advanced technologies innovative technical solution handling time dependencies grey wolf optimization experimental results show effectively capture patterns customer historical behaviors 65 %, rmse 0 %, 21 traditional method plawiak paper performs well optimizing key parameters dimensional financial data credit score prediction cnn performs well 51 %, 4 5 %, 68 limited prediction performance gwo model proposed 4 %, traditional methods paper proposes overall performance key component gwo algorithm financial industry financial field xlink "> significantly improving risk management hyperparameter tuning generalization ability fully capturing feature extraction existing methods digital transformation deep learning combines cnns |
| status_str | publishedVersion |
| title | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| title_full | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| title_fullStr | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| title_full_unstemmed | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| title_short | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| title_sort | The Model efficiency verification and comparison result on Taiwan Credit Default Data and Home Credit Default Risk Data. |
| topic | Ecology Science Policy Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified lendingclub loan dataset integrating advanced technologies innovative technical solution handling time dependencies grey wolf optimization experimental results show effectively capture patterns customer historical behaviors 65 %, rmse 0 %, 21 traditional method plawiak paper performs well optimizing key parameters dimensional financial data credit score prediction cnn performs well 51 %, 4 5 %, 68 limited prediction performance gwo model proposed 4 %, traditional methods paper proposes overall performance key component gwo algorithm financial industry financial field xlink "> significantly improving risk management hyperparameter tuning generalization ability fully capturing feature extraction existing methods digital transformation deep learning combines cnns |