Rule Based Systems for Big Data A Machine Learning Approach /

• Κύριοι συγγραφείς: Liu, Han (Συγγραφέας), Gegov, Alexander (Συγγραφέας), Cocea, Mihaela (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Έκδοση: 1st ed. 2015.
• Σειρά: Studies in Big Data, 13
• Θέματα: Engineering.; Data mining.; Artificial intelligence.; Computational intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).; Data Mining and Knowledge Discovery.
• Φυσική περιγραφή: XIII, 121 p. 38 illus., 5 illus. in color. online resource.
• ISBN: 9783319236964
• ISSN: 2197-6503 ;

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.