Multistrategy Learning

Name: Multistrategy Learning
Brand: Springer, Berlin
SKU: 9780792393740
Price: 1154.67 RON
Availability: InStock

A Special Issue of MACHINE LEARNING

Autor: Ryszard S. Michalski

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Legare: Copertă tare

Editura: Springer, Berlin

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Most machine learning research has been concerned with the development of systems that implememnt on...

Informații despre carte

Autor

Ryszard S. Michalski

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

1993

Pagini

155

EAN

9780792393740

ISBN

0792393740

Enbook ID

01398200

Editura

Springer, Berlin

Greutate

417

Dimensiuni

156 x 234 x 11

Descriere completă

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.

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Multistrategy Learning

A Special Issue of MACHINE LEARNING

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