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OverviewThe 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. Full Product DetailsAuthor: Han Liu , Alexander Gegov , Mihaela CoceaPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: Softcover reprint of the original 1st ed. 2016 Volume: 13 Weight: 2.175kg ISBN: 9783319370279ISBN 10: 3319370278 Pages: 121 Publication Date: 23 August 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsThe text is easily readable and nicely organized, deploying gradually the most important aspects encountered in the theory and practice of rule-based systems. ... the book is recommended to researchers and practitioners who wish to apply sound methods for understanding and exploiting their big data, and for those who plan to direct their research toward rule-based methodologies. (Lefteris Angelis, Computing Reviews, computingreviews.com, May, 2016) Author InformationTab Content 6Author Website:Countries AvailableAll regions |