Carte Multistrategy Learning Ryszard S. Michalski

Multistrategy Learning

A Special Issue of MACHINE LEARNING

Limbă: engleză
Legare: Carte broșată
Editura: Springer, Berlin
Disponibilitate: În depozitul extern
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1 104.81 lei
Most machine learning research has been concerned with the development of systems that implememnt on...

Informații despre carte

Limbă
engleză
Legare
Carte - Carte broșată
Publicat
2012
Pagini
155
EAN
9781461364054
ISBN
1461364051
Enbook ID
02076575
Greutate
260
Dimensiuni
155 x 235 x 9

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 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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