Municipal creditworthiness modelling by kernel-based approaches with supervised and semi-supervised learning

Abstract

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. © 2009 Springer-Verlag.