Feature selection in corporate credit rating prediction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F13%3A39896253" target="_blank" >RIV/00216275:25410/13:39896253 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S0950705113002104" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0950705113002104</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.knosys.2013.07.008" target="_blank" >10.1016/j.knosys.2013.07.008</a>

Result language
angličtina
Original language name
Feature selection in corporate credit rating prediction
Original language description
Credit rating assessment is a complicated process in which many parameters describing a company are taken into consideration and a grade is assigned, which represents the reliability of a potential client. Such assessment is expensive, because domain experts have to be employed to perform the rating. One way of lowering the costs of performing the rating is to use an automated rating procedure. In this paper, we assess several automatic classification methods for credit rating assessment. The methods presented in this paper follow a well-known paradigm of supervised machine learning, where they are first trained on a dataset representing companies with a known credibility, and then applied to companies with unknown credibility. We employed a procedureof feature selection that improved the accuracy of the ratings obtained as a result of classification. In addition, feature selection reduced the number of parameters describing a company that have to be known before the automatic rating
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AE - Management, administration and clerical work
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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