When comparing methods for classification, often the rating relies on their prediction accuracy alone. One reason for this is that this is the aspect that can be most easily measured. Yet, often one wants to learn more about the problem than only how to predict. The interpretation of the...

We use Dynamic Bayesian networks to classify business cycle phases. We compare classifiers generated by learning the Dynamic Bayesian network structure on different sets of admissible network structures. Included are sets of network structures of the Tree Augmented Naive Bayes (TAN) classifiers...

This paper is based on an article of Pumplün et al. (2005a) that investigates the use of Design of Experiments in data bases in order to select variables that are relevant for classification in situations where a sufficient number of measurements of the explanatory variables is available, but...

This paper discusses whether differences in the data structure of observational and experimental studies should lead to different strategies for variable selection. On the one hand, it is argued that outliers in the predictor variables have to be treated differently in the two kinds of studies....

In this paper business cycles are considered as a multivariate phenomenon and not as a univariate one determined e.g. by the GNP. The subject is to look for the number of phases of a business cycle, which can be motivated by the number of clusters in a given dataset of macro-economic variables....