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Multistrategy Learning

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Release : 1993-06-30
Genre : Computers
Kind : eBook
Book Rating : 740/5 ( reviews)

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Book Synopsis Multistrategy Learning by : Ryszard S. Michalski

Download or read book Multistrategy Learning written by Ryszard S. Michalski. This book was released on 1993-06-30. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multistrategy Learning

Download Multistrategy Learning PDF Online Free

Author :
Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 027/5 ( reviews)

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Book Synopsis Multistrategy Learning by : Ryszard S. Michalski

Download or read book Multistrategy Learning written by Ryszard S. Michalski. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Multistrategy Learning

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Author :
Release : 2003
Genre : Artificial intelligence
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Multistrategy Learning by : Ryszard Stanisław Michalski

Download or read book Multistrategy Learning written by Ryszard Stanisław Michalski. This book was released on 2003. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning

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Author :
Release : 1994-02-09
Genre : Computers
Kind : eBook
Book Rating : 519/5 ( reviews)

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Book Synopsis Machine Learning by : Ryszard S. Michalski

Download or read book Machine Learning written by Ryszard S. Michalski. This book was released on 1994-02-09. Available in PDF, EPUB and Kindle. Book excerpt: Multistrategy learning is one of the newest and most promising research directions in the development of machine learning systems. The objectives of research in this area are to study trade-offs between different learning strategies and to develop learning systems that employ multiple types of inference or computational paradigms in a learning process. Multistrategy systems offer significant advantages over monostrategy systems. They are more flexible in the type of input they can learn from and the type of knowledge they can acquire. As a consequence, multistrategy systems have the potential to be applicable to a wide range of practical problems. This volume is the first book in this fast growing field. It contains a selection of contributions by leading researchers specializing in this area. See below for earlier volumes in the series.

The Mathematical Foundation of Multi-Space Learning Theory

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Release : 2024-03-12
Genre : Education
Kind : eBook
Book Rating : 803/5 ( reviews)

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Book Synopsis The Mathematical Foundation of Multi-Space Learning Theory by : Tai Wang

Download or read book The Mathematical Foundation of Multi-Space Learning Theory written by Tai Wang. This book was released on 2024-03-12. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the measurement of learning effectiveness and the optimization of knowledge retention by modeling the learning process and building the mathematical foundation of multi-space learning theory. Multi-space learning is defined in this book as a micro-process of human learning that can take place in more than one space, with the goal of effective learning and knowledge retention. This book models the learning process as a temporal sequence of concept learning, drawing on established principles and empirical evidence. It also introduces the matroid to strengthen the mathematical foundation of multi-space learning theory and applies the theory to vocabulary and mathematics learning, respectively. The results show that, for vocabulary learning, the method can be used to estimate the effectiveness of a single learning strategy, to detect the mutual interference that might exist between learning strategies, and to predict the optimal combination of strategies. In mathematical learning, it was found that timing is crucial in both first learning and second learning in scheduling optimization to maximize the intersection effective interval. The title will be of interest to researchers and students in a wide range of areas, including educational technology, learning sciences, mathematical applications, and mathematical psychology.

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