Liu / Gegov / Cocea Rule Based Systems for Big Data

A Machine Learning Approach
1. Auflage 2015
ISBN: 978-3-319-23696-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 13, 127 Seiten, eBook

Reihe: Studies in Big Data

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.

Zielgruppe

Research

Autoren/Hrsg.

Liu, Han

Gegov, Alexander

Cocea, Mihaela

Inhaltsverzeichnis

Introduction.- Theoretical Preliminaries.- Generation of Classification Rules.- Simplification of Classification Rules.- Representation of Classification Rules.- Ensemble Learning Approaches.- Interpretability Analysis.