Rule Based Systems for Big Data: A Machine Learning Approach: 13 (Studies in Big Data, 13) - Hardcover

Liu, Han; Gegov, Alexander; Cocea, Mihaela

Hardcover

ISBN 10: 3319236954 ISBN 13: 9783319236957

Publisher: Springer, 2015

Synopsis

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data.

The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

About this title

From the Back Cover

The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data.

The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

Edition details

• Publisher: Springer
• Publication date: 2015
• Language: English
• ISBN 10: 3319236954
• ISBN 13: 9783319236957
• Binding: Hardcover
• Edition number: 1
• Number of pages: 134