In this paper, we examine the German business cycle (from 1955 to 1994) in order to identify univariate and multivariate outliers as well as influence points corresponding to Linear Discriminant Analysis. The locations of the corresponding observations are compared and economically interpreted.

This paper illustrates the Support Vector Method for the classification problem with two and more classes. In particular, the multi-class classification Support Vector Method of Weston and Watkins (1998) is correctly formulated as a quadratic optimization problem. Then, the method is applied to...

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...

In classification, with an increasing number of variables, the required number of observations grows drastically. In this paper we present an approach to put into effect the maximal possible variable selection, by splitting a K class classification problem into pairwise problems. The principle...

Linear Discriminant Analysis (LDA) performs well for classifica- tion of business phases even though the premises of an LDA are not met. As the variables are highly correlated there are numerical as well as interpretational shortcomings. By transforming the classification problem to a regression...