The Springer International Series in Engineering and Computer Science

Feature Selection for Knowledge Discovery and Data Mining

Authors: Huan Liu, Motoda, Hiroshi

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  • ISBN 978-1-4615-5689-3
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About this book

As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com­ puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys­ tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Table of contents (7 chapters)

  • Data Processing and Knowledge Discovery in Databases

    Liu, Huan (et al.)

    Pages 1-15

  • Perspectives of Feature Selection

    Liu, Huan (et al.)

    Pages 17-41

  • Feature Selection Aspects

    Liu, Huan (et al.)

    Pages 43-72

  • Feature Selection Methods

    Liu, Huan (et al.)

    Pages 73-95

  • Evaluation and Application

    Liu, Huan (et al.)

    Pages 97-149

Buy this book

eBook $279.00
price for USA (gross)
  • ISBN 978-1-4615-5689-3
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $359.00
price for USA
  • ISBN 978-0-7923-8198-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $359.00
price for USA
  • ISBN 978-1-4613-7604-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Feature Selection for Knowledge Discovery and Data Mining
Authors
Series Title
The Springer International Series in Engineering and Computer Science
Series Volume
454
Copyright
1998
Publisher
Springer US
Copyright Holder
Kluwer Academic Publishers
eBook ISBN
978-1-4615-5689-3
DOI
10.1007/978-1-4615-5689-3
Hardcover ISBN
978-0-7923-8198-3
Softcover ISBN
978-1-4613-7604-0
Series ISSN
0893-3405
Edition Number
1
Number of Pages
XXIII, 214
Topics