Multistrategy Learning - Couverture rigide

Couverture rigide

ISBN 10 : 0792393740 ISBN 13 : 9780792393740

Editeur : Kluwer Academic Publishers, 1993

Synopsis

Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined.
Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community.
Multistrategy Learning contains contributions characteristic of the current research in this area.

Détails de l'édition

• Éditeur: Kluwer Academic Publishers
• Date d'édition: 1993
• Langue: anglais
• ISBN 10: 0792393740
• ISBN 13: 9780792393740
• Reliure: Relié
• Numéro d'édition: 2
• Nombre de pages: 159
• Éditeur: Michalski Ryszard S.
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne