Appraisal of companies with Bayesian networks
International Journal of Business Intelligence and Data Mining
Bayesian belief network for box-office performance: A case study on Korean movies
Expert Systems with Applications: An International Journal
Confidence intervals for probabilistic network classifiers
Computational Statistics & Data Analysis
Behavioral assessment of recoverable credit of retailer's customers
Information Sciences: an International Journal
Hi-index | 0.00 |
In this paper, we will evaluate the power and usefulness of Bayesian network classifiers (probabilistic networks) for credit scoring. Various types of Bayesian network classifiers will be evaluated and contrasted including unrestricted Bayesian network classifiers learned using Markov Chain Monte Carlo (MCMC) search. The experiments will be carried out on three real life credit scoring data sets. It will be shown that MCMC Bayesian network classifiers have a very good performance and by using the Markov Blanket concept, a natural form of feature selection is obtained, which results in parsimonious and powerful models for financial credit scoring.