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Foundations of Rule Learning

By: Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač

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Foundations of Rule Learning

By: Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač

Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning. The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.

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Page Count

345

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540751971

ISBN 13

9783540751977

Foundations of Rule Learning

By: Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač

Write a review Read reviews Take a Quiz Solve Book Puzzle

Foundations of Rule Learning

By: Johannes Fürnkranz,Dragan Gamberger,Nada Lavrač

Rules – the clearest, most explored and best understood form of knowledge representation – are particularly important for data mining, as they offer the best tradeoff between human and machine understandability. This book presents the fundamentals of rule learning as investigated in classical machine learning and modern data mining. It introduces a feature-based view, as a unifying framework for propositional and relational rule learning, thus bridging the gap between attribute-value learning and inductive logic programming, and providing complete coverage of most important elements of rule learning. The book can be used as a textbook for teaching machine learning, as well as a comprehensive reference to research in the field of inductive rule learning. As such, it targets students, researchers and developers of rule learning algorithms, presenting the fundamental rule learning concepts in sufficient breadth and depth to enable the reader to understand, develop and apply rule learning techniques to real-world data.

Average ratings

N/A

5

0%

4

0%

3

0%

2

0%

1

0%

Solve jigsaw puzzle

Age

Page Count

345

Publisher

Springer Science & Business Media

Published Date

ISBN 10

3540751971

ISBN 13

9783540751977