This paper discusses issues related to Bayesian network model learning for unbalanced binary classification tasks. In general, the primary focus of current research on Bayesian ne...
Abstract. An important problem in biology is to understand correspondences between mRNA microarray levels and mass spectrometry peptide counts. Recently, a compendium of mRNA expre...
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
In this paper, we will evaluate the power and usefulness of Bayesian network classifiers for credit scoring. Various types of Bayesian network classifiers will be evaluated and co...
Bart Baesens, Michael Egmont-Petersen, Robert Cast...