EconPapers    
Economics at your fingertips  
 

Heteroscedastic Discriminant Analysis Combined With Feature Selection For Credit Scoring

Tomasz Smolarczyk (), Katarzyna Stąpor () and Piotr Fabian ()

Statistics in Transition new series, 2016, vol. 17, issue 2, 265-280

Abstract: Credit granting is a fundamental question and one of the most complex tasks that every credit institution is faced with. Typically, credit scoring databases are often large and characterized by redundant and irrelevant features. An effective classification model will objectively help managers instead of intuitive experience. This study proposes an approach for building a credit scoring model based on the combination of heteroscedastic extension (Loog, Duin, 2002) of classical Fisher Linear Discriminant Analysis (Fisher, 1936, Krzyśko, 1990) and a feature selection algorithm that retains sufficient information for classification purpose. We have tested five feature subset selection algorithms: two filters and three wrappers. To evaluate the accuracy of the proposed credit scoring model and to compare it with the existing approaches we have used the German credit data set from the study (Chen, Li, 2010). The results of our study suggest that the proposed hybrid approach is an effective and promising method for building credit scoring models.

Keywords: heteroscedastic discriminant analysis; feature subset selection; variable importance; credit scoring model (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v17_2016_i2_n8.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:csb:stintr:v:17:y:2016:i:2:p:265-280

Access Statistics for this article

Statistics in Transition new series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition new series from Główny Urząd Statystyczny (Polska) Contact information at EDIRC.
Bibliographic data for series maintained by Beata Witek ( this e-mail address is bad, please contact ).

 
Page updated 2021-03-28
Handle: RePEc:csb:stintr:v:17:y:2016:i:2:p:265-280