Hybrid techniques of combinatorial optimization based on genetic algorithms with application to feature selection in retail credit risk assessment
The purpose of this dissertation is to thoroughly investigate the overall data set available to the bank and to determine the extent to which these data can be a good basis for predicting the credit worthiness of the loan applicant. Such a prediction of the applicants ability should be done without seeking additional information from the client, assuming that the loan applicant is a lo…
Сътрудници
- Kliček, Božidar
Създател
- Oreški, Stjepan
Издател
- University of Zagreb. Faculty of Organization and Informatics Varaždin.
Тема
- hybrid techniques
- classification
- feature selection
- credit risk
- genetic algorithm
- neural networks
- SOCIAL SCIENCES. Information and Communication Sciences. Information Systems and Information Science.
- Computer science and technology. Computing. Data processing
Вид на обекта
- info:eu-repo/semantics/doctoralThesis
- text
Дата
- 2014-10-14
- 2014-10-14
Сътрудници
- Kliček, Božidar
Създател
- Oreški, Stjepan
Издател
- University of Zagreb. Faculty of Organization and Informatics Varaždin.
Тема
- hybrid techniques
- classification
- feature selection
- credit risk
- genetic algorithm
- neural networks
- SOCIAL SCIENCES. Information and Communication Sciences. Information Systems and Information Science.
- Computer science and technology. Computing. Data processing
Вид на обекта
- info:eu-repo/semantics/doctoralThesis
- text
Дата
- 2014-10-14
- 2014-10-14
доставчик на данни
Права за ползване на медиите в този обект (освен ако не е посочено друго)
- http://rightsstatements.org/vocab/InC/1.0/
Идентификатор
- https://dr.nsk.hr/islandora/object/foi:1142
- https://urn.nsk.hr/urn:nbn:hr:211:466344
- https://repozitorij.unizg.hr/islandora/object/foi:1142
- https://dr.nsk.hr/islandora/object/foi%3A1142/datastream/TN/view/
Формат
- application/pdf
Език
- hrv
Предоставяне на държава
- Croatia
Име на колекцията
Публикуван за първи път в Europeana
- 2019-04-05T13:44:09.391Z
Последно актуализиран от предоставящата институция
- 2019-04-05T13:44:09.391Z