Paper Info
Title
Bayesian Classification Trees with Overlapping Leaves Applied to Credit-Scoring
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.
Year
DOI
Venue
1998
10.1007/3-540-64383-4_20
PAKDD
Keywords
Field
DocType
bayesian classification trees,overlapping leaves,classification tree,bayesian classification,markov chain monte carlo
Information theory,Information processing,Naive Bayes classifier,Pattern recognition,Markov chain Monte Carlo,Computer science,Markov chain,Posterior probability,Artificial intelligence,Machine learning,Bayesian probability
Conference
Volume
ISSN
ISBN
1394
0302-9743
3-540-64383-4
Citations 
PageRank 
References 
4
0.55
2
Authors
2
Name
Order
Citations
PageRank
Gerhard Paass1113683.63
Jörg Kindermann241133.66