Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervised Learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F09%3A00009337" target="_blank" >RIV/00216275:25410/09:00009337 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervised Learning
Original language description
The paper presents the modelling possibilities of kernel-based approaches on a complex real-world problem, i.e. municipal creditworthiness classification. A model design includes data pre-processing, labelling of individual parameters' vectors using expert knowledge, and the design of various support vector machines with supervised learning and kernel-based approaches with semi-supervised learning.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
AE - Management, administration and clerical work
OECD FORD branch
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Result continuities
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)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Engineering Applications of Neural Networks - EANN 2009: 11th International Conference on Engineering
ISBN
978-3-642-03968-3
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
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Publisher name
Springer
Place of publication
Dordrecht
Event location
London, UK
Event date
Aug 29, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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