Rule Based Systems for Big Data

A Machine Learning Approach
Softcover Nachdruck of the original 1. Auflage 2016
ISBN: 978-3-319-37027-9
Verlag: Springer International Publishing

Buch, Englisch, Band 13, 121 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 2175 g

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

Cocea, Mihaela

Gegov, Alexander

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

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