Optimization for pattern classification using biased random search techniques

The authors demonstrate how optimization problems arise in the field of pattern classification, in particular in using piecewise-linear classification and classification based on an optimal linear separator. They motivate the need in this area for a general purpose optimization approach. The authors discuss ALOPEX, a bias random search approach, from the point of view of this need. While ALOPEX itself failed to fulfil the present need, a newly-introduced generalization of it (iterated ALOPEX) was found to be appropriate for the optimization problems of the particular concern. They conclude the paper with a brief critical evaluation of this approach as compared to the present original aims.