Feature Extraction, Construction and Selection

Name: Feature Extraction, Construction and Selection
Brand: Springer, Berlin
SKU: 9781461376224
Price: 845.73 PLN
Availability: InStock

A Data Mining Perspective

Autor: Huan Liu, Hiroshi Motoda

Język:

Oprawa: Miękka

Wydawca: Springer, Berlin

Dostępność: Dostępna u dostawcy

Wysyłamy za 5-8 dni

845.73 zł

There is broad interest in feature extraction, construction, and selection among practitioners from...

Informacje o książce

Autor

Huan Liu, Hiroshi Motoda

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2013

strony

410

EAN

9781461376224

ISBN

146137622X

Enbook ID

06797006

Wydawca

Springer, Berlin

Waga

670

Wymiary

155 x 235 x 22

Pełny opis

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.

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A Data Mining Perspective

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