Multistrategy Learning : A Special Issue of MACHINE LEARNING

Language: English

Published by Springer Nature B.V. Jun 1993, 1993

0792393740 / 9780792393740

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Neuware - 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.…

Seller Inventory # 9780792393740

Title
Multistrategy Learning : A Special Issue of MACHINE LEARNING
Author
Ryszard S. Michalski
Publisher
Springer Nature B.V. Jun 1993
Publication year
1993
Condition
Neu
Binding
Buch
Language
English
ISBN 10
0792393740
ISBN 13
9780792393740
Item weight
410 grams
Dimensions
234x156x11 mm

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