2009 | OriginalPaper | Buchkapitel
Municipal Creditworthiness Modelling by Kernel-Based Approaches with Supervised and Semi-supervised Learning
verfasst von : Petr Hajek, Vladimir Olej
Erschienen in: Engineering Applications of Neural Networks
Verlag: Springer Berlin Heidelberg
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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.