Foundations of Rule Learning

Essentials of Machine Learning and Relational Data Mining

Furnkranz, Johannes / Gamberger, Draqan / Lavrac, Nada

Genre: books4me > Computers & The Internet > Computer - Databases

Format: Book - Hardcover

Released: Thu 29 Mar 2012

Catalogue Number: 0009452287

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AUD$151.48

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Description:
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.

Details:

Publisher: Springer-Verlag New York Inc
Series: Cognitive Technologies
Academic Level: Scholarly/Undergraduate
Dewey: 005
Edition: 1
Place Of Publication: United States
Published Date: Thu 29 Mar 2012

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