The Resource Learning from data : concepts, theory, and methods, Vladimir Cherkassky, Filip Mulier, (electronic resource)

Learning from data : concepts, theory, and methods, Vladimir Cherkassky, Filip Mulier, (electronic resource)

Label
Learning from data : concepts, theory, and methods
Title
Learning from data
Title remainder
concepts, theory, and methods
Statement of responsibility
Vladimir Cherkassky, Filip Mulier
Creator
Contributor
Provider
Publisher
Subject
Language
eng
Summary
An interdisciplinary framework for learning methodologies--covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied--showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science
Cataloging source
IEEEE
http://library.link/vocab/creatorName
Cherkassky, Vladimir S
Illustrations
illustrations
Index
index present
LC call number
TK5102.9
LC item number
.C475 2007
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
  • Mulier, Filip
  • IEEE Xplore
  • John Wiley & Sons
  • Institute of Electrical and Electronics Engineers
http://library.link/vocab/subjectName
  • Adaptive signal processing
  • Machine learning
  • Neural networks (Computer science)
  • Fuzzy systems
  • COMPUTERS
  • COMPUTERS
  • Statistisch onderzoek
  • Statistische methoden
  • Computermodellen
  • Datenauswertung
  • Maschinelles Lernen
  • Methode
Label
Learning from data : concepts, theory, and methods, Vladimir Cherkassky, Filip Mulier, (electronic resource)
Instantiates
Publication
Note
Made available via IEEE Xplore Digital Library
Bibliography note
Includes bibliographical references (p. 519-531) and index
Color
multicolored
Contents
Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource (xviii, 538 p.)
Form of item
online
Isbn
9780470140512
Other control number
10.1002/9780470140529
Other physical details
ill.
Specific material designation
remote
Stock number
9780470140529
System control number
  • (OCoLC)668993792
  • (OCoLC)ocn668993792
Label
Learning from data : concepts, theory, and methods, Vladimir Cherkassky, Filip Mulier, (electronic resource)
Publication
Note
Made available via IEEE Xplore Digital Library
Bibliography note
Includes bibliographical references (p. 519-531) and index
Color
multicolored
Contents
Problem statement, classical approaches, and adaptive learning -- Regularization framework -- Statistical learning theory -- Nonlinear optimization strategies -- Methods for data reduction and dimensionality reduction -- Methods for regression -- Classification -- Support vector machines -- Noninductive inference and alternative learning formulations
Dimensions
unknown
Edition
2nd ed.
Extent
1 online resource (xviii, 538 p.)
Form of item
online
Isbn
9780470140512
Other control number
10.1002/9780470140529
Other physical details
ill.
Specific material designation
remote
Stock number
9780470140529
System control number
  • (OCoLC)668993792
  • (OCoLC)ocn668993792

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