Multistrategy Learning: A Special Issue of MACHINE LEARNING (The Springer International Series in Engineering and Computer Science, Band 240) - Softcover

Softcover

ISBN 10: 1461364051 ISBN 13: 9781461364054

Verlag: Springer, 2012

Inhaltsangabe

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.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2012
• Sprache: Englisch
• ISBN 10: 1461364051
• ISBN 13: 9781461364054
• Einband: Taschenbuch
• Anzahl der Seiten: 164
• Herausgeber: Michalski Ryszard S.
• Kontakt zum Hersteller: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Deutschland