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A Survey of Applying Machine Learning Techniques for Credit Rating: Existing Models and Open Issues

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dc.contributor.author Wang, X.
dc.contributor.author Xu, M.
dc.contributor.author Pusatlı, Özgür Tolga
dc.date.accessioned 2020-05-06T19:31:17Z
dc.date.available 2020-05-06T19:31:17Z
dc.date.issued 2015
dc.identifier.citation Wang, X.; Xu, M.; Pusatli, Ö.T., "A Survey of Applying Machine Learning Techniques for Credit Rating: Existing Models and Open Issues", Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9490, (2015). tr_TR
dc.identifier.isbn 978-331926534-6
dc.identifier.issn 03029743
dc.identifier.uri http://hdl.handle.net/20.500.12416/3640
dc.description.abstract In recent years, machine learning techniques have been widely applied for credit rating. To make a rational comparison of performance of different learning-based credit rating models, we focused on those models that are constructed and validated on the two mostly used Australian and German credit approval data sets. Based on a systematic review of literatures, we further compare and discuss about the performance of existing models. In addition, we identified and illustrated the limitations of existing works and discuss about some open issues that could benefit future research in this area. tr_TR
dc.language.iso eng tr_TR
dc.publisher Springer Verlag tr_TR
dc.relation.isversionof 10.1007/978-3-319-26535-3_15 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Hybrid Learning Models tr_TR
dc.subject Credit Rating tr_TR
dc.subject Literature Survey tr_TR
dc.subject Single Classifier Models tr_TR
dc.title A Survey of Applying Machine Learning Techniques for Credit Rating: Existing Models and Open Issues tr_TR
dc.type bookPart tr_TR
dc.relation.journal Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) tr_TR
dc.contributor.authorID 51704 tr_TR
dc.identifier.volume 9490 tr_TR
dc.identifier.startpage 122 tr_TR
dc.identifier.endpage 132 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen Edebiyat Fakültesi, Matematik Bölümü tr_TR


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