The Resource Interpretability of Computational Intelligence-Based Regression Models, by Tamás Kenesei, János Abonyi, (electronic resource)

Interpretability of Computational Intelligence-Based Regression Models, by Tamás Kenesei, János Abonyi, (electronic resource)

Label
Interpretability of Computational Intelligence-Based Regression Models
Title
Interpretability of Computational Intelligence-Based Regression Models
Statement of responsibility
by Tamás Kenesei, János Abonyi
Creator
Contributor
Author
Provider
Subject
Language
eng
Summary
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
Member of
http://library.link/vocab/creatorName
Kenesei, Tamás
Image bit depth
0
LC call number
  • Q334-342
  • TJ210.2-211.495
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
  • Abonyi, János.
  • SpringerLink
Series statement
SpringerBriefs in Computer Science,
http://library.link/vocab/subjectName
  • Computer science
  • Data mining
  • Artificial intelligence
  • Computational intelligence
  • Computer Science
  • Artificial Intelligence (incl. Robotics)
  • Computational Intelligence
  • Data Mining and Knowledge Discovery
Label
Interpretability of Computational Intelligence-Based Regression Models, by Tamás Kenesei, János Abonyi, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Interpretability of Hinging Hyperplanes -- Interpretability of Neural Networks -- Interpretability of Support Vector Machines -- Summary
Dimensions
unknown
Edition
1st ed. 2015.
Extent
X, 82 p. 34 illus., 14 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319219424
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-21942-4
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-319-21942-4
Label
Interpretability of Computational Intelligence-Based Regression Models, by Tamás Kenesei, János Abonyi, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Interpretability of Hinging Hyperplanes -- Interpretability of Neural Networks -- Interpretability of Support Vector Machines -- Summary
Dimensions
unknown
Edition
1st ed. 2015.
Extent
X, 82 p. 34 illus., 14 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319219424
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-21942-4
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-319-21942-4

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