Advances in predictive models for data mining

Expanding application demand for data mining of massive data warehouses has fueled advances in automated predictive methods. We examine a few successf ul application areas and their technical challenges. We review the key theo retical developments in PAC and statistical learning theory that have lead to the development of support vector machines and to the use of multiple mo dels for increased predictive accuracy. (C) 2001 Elsevier Science B.V. All rights reserved.