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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Multistrategy Learning
• Podnázev: A Special Issue of MACHINE LEARNING
• Autor: Ryszard S. Michalski
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 155
• EAN: 9780792393740
• ISBN: 0792393740
• ID: 01398200
• Nakladatelství: Springer, Berlin
• Hmotnost: 417 g
• Rozměry: 234 × 156 × 11 mm
• Rok vydání: 1993

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