Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F11%3A39882095" target="_blank" >RIV/00216275:25410/11:39882095 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/s00521-010-0495-0" target="_blank" >http://dx.doi.org/10.1007/s00521-010-0495-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s00521-010-0495-0" target="_blank" >10.1007/s00521-010-0495-0</a>

Result language
angličtina
Original language name
Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning
Original language description
This paper presents the modelling possibilities of kernel-based approaches to a complex real-world problem, i.e. corporate and municipal credit rating classification. Based on a model design that includes data pre-processing, the labelling of individualparameter vectors using expert knowledge, the design of various support vector machines with supervised learning as well as kernel-based approaches with semi-supervised learning, this modelling is undertaken in order to classify objects into rating classes. The results show that the rating classes assigned to bond issuers can be classified with high classification accuracy using a limited subset of input variables. This holds true for kernel-based approaches with both supervised and semi-supervised learning.
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
IN - Informatics
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
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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