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Feature Extraction, Construction and Selection

Feature Extraction, Construction and Selection

A Data Mining Perspective

by Hiroshi Motoda and Huan Liu
Paperback
Publication Date: 11/10/2012

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There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data preprocessing 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-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 the research of feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of our 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. Even with today's advanced computer technologies, discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Feature extraction, construction and selection are a set of techniques that transform and simplify data so as to make data mining tasks easier. Feature construction and selection can be viewed as two sides of the representation problem.
ISBN:
9781461376224
9781461376224
Category:
Algorithms & data structures
Format:
Paperback
Publication Date:
11-10-2012
Language:
English
Publisher:
Springer-Verlag New York Inc.
Country of origin:
United States
Pages:
410
Dimensions (mm):
235x155x22mm
Weight:
0.67kg

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