A Classification Problem Of Credit Risk Rating Investigated And Solved By New Methods Of Statistical Learning And Optimization

Date

2009-12-31

Author

Weber, Gerhard Wilhelm

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Bu proje gerçek hayat finans sektöründen esinlenilmiştir. Yaklaşımımız istatistiksel araç olan ROC eğrisinin optimizasyonu üzerinedir. İstatistiğin modelden bağımsız değil, modele dayalı matematik yaklaşımını kullanarak problemimiz için çözüm önerilebilir. Yeni yaklaşımımız kredilendirme ve kalite analiz ve kontrolü konularında klasik istatistik yöntemlerinden daha başarılı ve gerçekçidir. Ekteki bağlantıdaki döküman buna örnek teşkil eder. (http://144.122.137.55/gweber/ ve http://www.iam.metu.edu.tr/mscthesis/fatmayerlika yathesis.pdf). 2) Tanım: a) Konu ile ilgili literatür taraması; konunun güncel durumu ve bulunduğu aşama: ROC eğrisinin optimizasyonun yanı sıra, modelimizde en iyiyi elde etmek için dengelenmis sınıf sayılarına bakmaktayız. Gerçekte bu model, lineer olmaya modeller sınıfına girmektedir. Gauss-Newton ve Levenberg-Marquardt yöntemleri ile regüle edilmiş lineer regresyon teknikleri modeldeki her basamağı tanımlamakta kullanılmaktadır. Bu projeyle finans sektörüne

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https://hdl.handle.net/11511/61658

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Graduate School of Applied Mathematics, Project and Design

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Citation Formats

G. W. Weber, “A Classification Problem Of Credit Risk Rating Investigated And Solved By New Methods Of Statistical Learning And Optimization,” 2009. Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/61658.