Abstract
We develop a Bayesian procedure for classification with trees by switching between different model structures. For classification trees with overlap we use a Markov chain Monte Carlo procedure to produce an ensemble of trees which allow the assessment of prediction uncertainty and the value of new information. The approach is applied to a large credit scoring application.
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© 1998 Springer-Verlag Berlin Heidelberg
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Paass, G., Kindermann, J. (1998). Bayesian classification trees with overlapping leaves applied to credit-scoring. In: Wu, X., Kotagiri, R., Korb, K.B. (eds) Research and Development in Knowledge Discovery and Data Mining. PAKDD 1998. Lecture Notes in Computer Science, vol 1394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64383-4_20
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DOI: https://doi.org/10.1007/3-540-64383-4_20
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