We propose a computer intensive method for linear dimension reduction which minimizes the classification error directly. Simulated annealing (Bohachevsky et al 1986) as a modern optimization technique is used to solve this problem effectively. This approach easily allows to incorporate user...

A lot of alternatives and constraints have been proposed in order to improve the Fisher criterion. But most of them are not linked to the error rate, the primary interest in many applications of classification. By introducing an upper bound for the error rate a criterion is developed which can...

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 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.