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…
Bidragydere
- Kliček, Božidar
Skaberen
- Oreški, Stjepan
Udgiver
- University of Zagreb. Faculty of Organization and Informatics Varaždin.
Emne
- 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
Type af genstand
- info:eu-repo/semantics/doctoralThesis
- text
Dato
- 2014-10-14
- 2014-10-14
Bidragydere
- Kliček, Božidar
Skaberen
- Oreški, Stjepan
Udgiver
- University of Zagreb. Faculty of Organization and Informatics Varaždin.
Emne
- 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
Type af genstand
- info:eu-repo/semantics/doctoralThesis
- text
Dato
- 2014-10-14
- 2014-10-14
Aggregator
Rettigheder for medierne i denne optagelse (medmindre andet er angivet)
- http://rightsstatements.org/vocab/InC/1.0/
Identifikator
- 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/
Format
- application/pdf
Sprog
- hrv
Leverende land
- Croatia
Navn på samling
Første gang offentliggjort på Europeana
- 2019-04-05T13:44:09.391Z
Sidste gang opdateret fra den ejerinstiution
- 2019-04-05T13:44:09.391Z