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Feature Extraction, Construction and Selection: A Data Mining Perspective (The Springer International Series in Engineering and Computer Science)

Liu, Huan, Huan, Liu

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ISBN 10: 0792381963 / ISBN 13: 9780792381969
Published by Springer
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About this Item

Data pre-processing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from researchers in this field and offers the techniques that can boost the capabilities of many data mining tools. It is suitable for researchers and graduate students in machine learning and data mining. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 434 pages, biography. BIC Classification: UN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 235 x 155 x 25. Weight in Grams: 791. . 1998. 1998th Edition. Hardcover. . . . . Bookseller Inventory # V9780792381969

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Title: Feature Extraction, Construction and ...

Publisher: Springer

Binding: Hardcover

Book Condition:New

About this title

Synopsis:

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.

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