Credit Risk Models Using Machine Learning Models
| dc.contributor.advisor | Çakar, Tuna | |
| dc.contributor.author | Akman, Özkan | |
| dc.date.accessioned | 2019-11-12T13:41:59Z | |
| dc.date.available | 2019-11-12T13:41:59Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Credit scoring is an important subject in financial institutions, mainly in banks. I want to examine some machine learning techniques to find out a model that performs good in predicting or classifying the loaner person a good credit or a bad one by evaluating his/her demographic features as marital status, wealth, job seniority, monthly income and expenses. | |
| dc.identifier.citation | Akman, Ö. (2018). Credit risk models using machine learning models, MEF Üniversitesi Fen Bilimleri Enstitüsü, İstanbul, Türkiye | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11779/1157 | |
| dc.language.iso | en | |
| dc.publisher | MEF Üniversitesi, Fen Bilimleri Enstitüsü | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Credit Ranking | |
| dc.subject | Credit Scoring Models | |
| dc.subject | Machine Learning | |
| dc.subject | Support Vector Machine | |
| dc.subject | Decision Tree Model | |
| dc.subject | Linear Discrimant Analysis | |
| dc.subject | Loan-to-Value Ration | |
| dc.subject | Saving Capacity | |
| dc.subject | Logistic Regression Model | |
| dc.title | Credit Risk Models Using Machine Learning Models | |
| dc.title.alternative | Makine öğrenmesi uygulamaları ile kredi risk modelleme | |
| dc.type | Master's Degree Project | |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Çakar, Tuna | |
| gdc.coar.access | open access | |
| gdc.coar.type | text::thesis::master thesis | |
| gdc.description.department | Lisansüstü Eğitim Enstitüsü, Büyük Veri Analitiği Yüksek Lisans Programı | |
| gdc.description.publicationcategory | YL-Bitirme Projesi | |
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