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Item Details
| Title:
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FEATURE EXTRACTION, CONSTRUCTION AND SELECTION
A DATA MINING PERSPECTIVE |
| By: |
Huan Liu (Editor), Hiroshi Motoda (Editor) |
| Format: |
Paperback |
| List price:
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£260.50 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
146137622X |
| ISBN 13: |
9781461376224 |
| Publisher: |
SPRINGER-VERLAG NEW YORK INC. |
| Pub. date: |
11 October, 2012 |
| Edition: |
Softcover reprint of the original 1st ed. 1998 |
| Series: |
The Springer International Series in Engineering and Computer Science 453 |
| Pages: |
410 |
| Description: |
There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Feature extraction, construction and selection are a set of techniques that transform and simplify data so as to make data mining tasks easier. |
| Synopsis: |
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. |
| Illustrations: |
XXIV, 410 p. |
| Publication: |
US |
| Imprint: |
Springer-Verlag New York Inc. |
| Returns: |
Returnable |
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