ENGLISH

Rule Based Systems for Big Data: A Machine Learning Approach

By Alexander Gegov , Mihaela Cocea , Han Liu

Book information

Publisher
Springer International Publishing
Year
2015
ISBN
3319236954, 978-3-319-23695-7, 978-3-319-23696-4
DOI
10.1007/978-3-319-23696-4
ASIN
978-3319236957
Language
english
Format
PDF
Filesize
3 MB (2933378 bytes)
Series
Studies in Big Data 13
Edition
1st
Pages
127\127
Time added
2015-10-01 10:37:13
Computational Intelligence; Artificial Intelligenc

Description

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.

Similar books