Feature Extraction, Construction and Selection
Subtitle: a Data Mining Perspective
By: edited by Huan Liu, Hiroshi Motoda
Contributors: Motoda, Hiroshi
Series: The Springer International Series in Engineering and Computer Science -- 453; International series in engineering and computer science -- 453.
Publisher: Springer US
Published: 1998
Place of publication: Boston, MA
Language: eng
Format: [electronic resource] :
Number of pages: 410
ISBN-13: 9781461376224; 9781461557258
Subjects: Statistics; Data structures (Computer science); Computer science; Artificial intelligence
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.
Notes: Online full text is restricted to subscribers.

Also available in print.

Mode of access: World Wide Web.