Téléchargez le livre :  Interpretability of Computational Intelligence-Based Regression Models
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János Abonyi , Tamás Kenesei

Interpretability of Computational Intelligence-Based Regression Models

Springer

Collection : SpringerBriefs in Computer Science

Date de publication : 2015-10-22



58,01
Guide des formats
Description

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.
Pages
82
Collection
SpringerBriefs in Computer Science
Parution
2015-10-22
Marque
Springer
EAN papier
9783319219417
EAN PDF
9783319219424

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
3195 Ko
Prix
58,01 €
EAN EPUB
9783319219424

Informations sur l'ebook
Nombre pages copiables
0
Nombre pages imprimables
8
Taille du fichier
1167 Ko
Prix
58,01 €