Bajeso metodo taikymas kreditų rizikos valdyme: atlikta įvairių egzistuojančių metodų rizikai valdyti tyrimas, pateiktas analitinėje dalyje, aprašyti kai kurie plačiau naudojami mašininio mokymo ir matematiniai modeliai. Paiūlytas modelis eksperimentui atlikti, atliktas empirinis tyrimas ir pateikti gauti rezultatai, pateiktos išvados ir ateities perspektyvos. / Baysan Method for a Credit Risk Management This paper presents a method combining popular machine learning technique for classification, genetic search as a feature selection method for relevant attribute selection and Altman Z-Score discriminant technique for credit risk evaluation. Bayesian method based classifiers (Naïve Bayes, Bayesian Networks) were explored and used in this article to train classifiers. This method was applied to different sectors in service and industry. Its performance was evaluated using weighted mean accuracy and weighted mean error techniques. In theoretical part several methods were analyzed and described, in the end conclusions and suggestions were pointed.
| Identifer | oai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2010~D_20110709_152459-96351 |
| Date | 09 July 2011 |
| Creators | Būzius, Gediminas |
| Contributors | Garšva, Gintautas, Vilnius University |
| Publisher | Lithuanian Academic Libraries Network (LABT), Vilnius University |
| Source Sets | Lithuanian ETD submission system |
| Language | Lithuanian |
| Detected Language | English |
| Type | Master thesis |
| Format | application/pdf |
| Source | http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20110709_152459-96351 |
| Rights | Unrestricted |
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