Multistrategy Learning

Name: Multistrategy Learning
Brand: Springer, Berlin
SKU: 9781461364054
Price: 210.35 EUR
Availability: InStock

A Special Issue of MACHINE LEARNING

Автор: Ryszard S. Michalski

Език:

Корици: С меки корици

Издател: Springer, Berlin

Наличност: Външен склад

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

Информация за книгата

Автор

Ryszard S. Michalski

Език

Английски език

Корици

Книга - С меки корици

Издадена

2012

страници

155

EAN

9781461364054

ISBN

1461364051

Enbook ID

02076575

Издател

Springer, Berlin

Теглоt

260

Размери

155 x 235 x 9

Пълно описание

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 m ultistrategy 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

Информация за книгата

Пълно описание

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