Interpretability of Computational Intelligence-Based Regression Models

Language: English

Published by Springer, Palgrave Macmillan Nov 2015, 2015

3319219413 / 9783319219417

Series: Book 189 of 322 - SpringerBriefs in Computer Science

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This item is printed on demand - Print on Demand Titel. Neuware -The key idea of this book is that hinging hyperplanes, neural networks and support vector machines can be transformed into fuzzy models, and interpretability of the resulting rule-based systems can be ensured by special model reduction and visualization techniques. The first part of the book deals with the identification of hinging hyperplane-based regression trees. The next part deals with the validation, visualization and structural reduction of neural networks based on the transformation of the hidden layer of the network into an additive fuzzy rule base system. Finally, based on the analogy of support vector regression and fuzzy models, a three-step model reduction algorithm is proposed to get interpretable fuzzy regression models on the basis of support vector regression.The authors demonstrate real-world use of the algorithms with examples taken from process engineering, and they support the text with downloadable Matlab code. The book is suitable for researchers, graduate students and practitioners in the areas of computational intelligence and machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch.…

Seller Inventory # 9783319219417

Title
Interpretability of Computational Intelligence-Based Regression Models
Author
Tamás Kenesei
Publisher
Springer, Palgrave Macmillan Nov 2015
Publication year
2015
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3319219413
ISBN 13
9783319219417
Item weight
154 grams
Dimensions
235x155x6 mm
Series
Book 189 of 322: SpringerBriefs in Computer Science

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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