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Interpretability of Computational Intelligence-Based Regression Models

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Interpretability of Computational Intelligence-Based Regression Models Tamás Kenesei
Koda Libristo: 09378357
Založba Springer International Publishing AG, oktober 2015
The key idea of this book is that hinging hyperplanes, neural networks and support vector machines c... Celoten opis
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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.§

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Polni naslov Interpretability of Computational Intelligence-Based Regression Models
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2015
Število strani 82
EAN 9783319219417
ISBN 3319219413
Koda Libristo 09378357
Teža 1533
Mere 155 x 235 x 8
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