Feature Extraction

Foundations and Applications

  • Isabelle Guyon
  • Masoud Nikravesh
  • Steve Gunn
  • Lotfi A. Zadeh

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 207)

Table of contents

  1. Front Matter
    Pages I-XXIV
  2. An Introduction to Feature Extraction

    1. Isabelle Guyon, André Elisseeff
      Pages 1-25
  3. Feature Extraction Fundamentals

    1. Front Matter
      Pages 27-27
    2. Norbert Jankowski, Krzysztof Grabczewski
      Pages 29-64
    3. Gérard Dreyfus, Isabelle Guyon
      Pages 65-88
    4. Włodzisław Duch
      Pages 89-117
    5. Juha Reunanen
      Pages 119-136
    6. Thomas Navin Lal, Olivier Chapelle, Jason Weston, André Elisseeff
      Pages 137-165
    7. Kari Torkkola
      Pages 167-185
    8. Eugene Tuv
      Pages 187-204
    9. Madan M. Gupta, Noriyasu Homma, Zeng-Guang Hou
      Pages 205-233
  4. Feature Selection Challenge

    1. Front Matter
      Pages 235-235
    2. Isabelle Guyon, Steve Gunn, Asa Ben Hur, Gideon Dror
      Pages 237-263
    3. Yi-Wei Chen, Chih-Jen Lin
      Pages 315-324
    4. Alexander Borisov, Victor Eruhimov, Eugene Tuv
      Pages 359-374

About this book

Introduction

This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction.
"This book compiles some very promising techniques, coming from an extremely smart collection of researchers, delivering their best ideas in a competitive environment."
Trevor Hastie, Stanford University
"Feature selection is a key technology for making sense of the high dimensional data. Isabelle Guyon et al. have done a splendid job in designing a challenging competition, and collecting the lessons learned."
Bernhard Schoelkopf, Max Planck Institute
"There has been until now insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons. This volume is noteworthy for the breadth of methods covered, the clarity of presentations, the unity in notation and the helpful statistical appendices."
David G. Stork, Ricoh Innovations
"Feature extraction finds application in biotechnology, industrial inspection, the Internet, radar, sonar, and speech recognition. This book will make a difference to the literature on machine learning."
Simon Haykin, Mc Master University
"This book sets a high standard as the public record of an interesting and effective competition."
Peter Norvig, Google Inc.

Keywords

Feature Extraction Feature Selection Fuzzy Machine Learning Statistical Learning algorithm algorithms calculus cognition learning learning theory linear optimization modeling sets speech recognition

Editors and affiliations

  • Isabelle Guyon
    • 1
  • Masoud Nikravesh
    • 2
  • Steve Gunn
    • 3
  • Lotfi A. Zadeh
    • 4
  1. 1.ClopinetBerkeleyUSA
  2. 2.Department of Electrical Engineering & Computer Science — EECSUniversity of CaliforniaBerkeleyUSA
  3. 3.School of Electronics and Computer SciencesUniversity of SouthamptonSouthampton HighfieldUK
  4. 4.Division of Computer Science Lab. Electronics ResearchUniversity of CaliforniaBerkeleyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-35488-8
  • Copyright Information Springer Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-35487-1
  • Online ISBN 978-3-540-35488-8
  • Series Print ISSN 1434-9922
  • About this book