Author

Contributions

  • Motoda, Hiroshi - Contributor

Publication

1998 - Springer US, Boston, MA, Massachusetts

Language

English

Word Count

102,500 words, Guess

Page Count

410 pages

Physical Format

Electronic resource

Identifiers

  • Internet Archivefeatureextractio00liuh
  • ISBN-10146137622X
  • ISBN-101461557259
  • ISBN-139781461376224
  • ISBN-139781461557258
and 4 more
  • OCLC Control Number851754448
  • Better World Books9781461376224
  • Better World Books9781461557258
  • Open LibraryOL27038297M

Classifications

  • DDC005.74
  • LCCQA76.9.D35
  • LCCQA76.9.D35QA276-280Q

Description

There is a broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data pre-processing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-the-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about research into feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of an endeavor to produce a contemporary overview of modern solutions, to create synergy among these seemingly different branches, and to pave the way for developing meta-systems and novel approaches. The book can be used by researchers and graduate students in machine learning, data mining, and knowledge discovery, who wish to understand techniques of feature extraction, construction and selection for data pre-processing and to solve large size, real-world problems. The book can also serve as a reference work for those who are conducting research into feature extraction, construction and selection, and are ready to meet the exciting challenges ahead of us.

Subjects

Other Editions

  • Feature Extraction, Construction and Selection: a Data Mining PerspectiveElectronic resourceSpringer US1998-01-01

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