Intelligent Systems Reference Library

Data Preprocessing in Data Mining

Authors: García, Salvador, Luengo, Julian, Herrera, Francisco

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  • Covers the set of techniques under the umbrella of data preprocessing in data mining and machine learning
  • A comprehensive book devoted completely to preprocessing in data mining
  • Written by experts in the field
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eBook $109.00
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  • ISBN 978-3-319-10247-4
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Hardcover $199.99
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Softcover $139.99
price for Mexico
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: 28 de octubre de 2016
  • ISBN 978-3-319-37731-5
  • Free shipping for individuals worldwide. Please be advised Covid-19 shipping restrictions apply. Please review prior to ordering
  • Usually ready to be dispatched within 3 to 5 business days
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About this book

Data Preprocessing for Data Mining addresses one of the most important issues within the well-known Knowledge Discovery from Data process. Data directly taken from the source will likely have inconsistencies, errors or most importantly, it is not ready to be considered for a data mining process. Furthermore, the increasing amount of data in recent science, industry and business applications, calls to the requirement of more complex tools to analyze it. Thanks to data preprocessing, it is possible to convert the impossible into possible, adapting the data to fulfill the input demands of each data mining algorithm. Data preprocessing includes the data reduction techniques, which aim at reducing the complexity of the data, detecting or removing irrelevant and noisy elements from the data.

This book is intended to review the tasks that fill the gap between the data acquisition from the source and the data mining process. A comprehensive look from a practical point of view, including basic concepts and surveying the techniques proposed in the specialized literature, is given.Each chapter is a stand-alone guide to a particular data preprocessing topic, from basic concepts and detailed descriptions of classical algorithms, to an incursion of an exhaustive catalog of recent developments. The in-depth technical descriptions make this book suitable for technical professionals, researchers, senior undergraduate and graduate students in data science, computer science and engineering.

Reviews

From the book reviews:

“This book is a comprehensive collection of data preprocessing techniques used in data mining. Any readers who practice data mining will find it beneficial … . This book is an excellent guideline in the topic of data preprocessing for data mining. It is suitable for both practitioners and researchers who would like to use datasets in their data mining projects.” (Xiannong Meng, Computing Reviews, December, 2014)

Table of contents (10 chapters)

Table of contents (10 chapters)

Buy this book

eBook $109.00
price for Mexico
  • ISBN 978-3-319-10247-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • Immediate eBook download after purchase and usable on all devices
  • Bulk discounts available
Hardcover $199.99
price for Mexico
Softcover $139.99
price for Mexico
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week). Pre-ordered printed titles are excluded from promotions.
  • Due: 28 de octubre de 2016
  • ISBN 978-3-319-37731-5
  • Free shipping for individuals worldwide. Please be advised Covid-19 shipping restrictions apply. Please review prior to ordering
  • Usually ready to be dispatched within 3 to 5 business days
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Data Preprocessing in Data Mining
Authors
Series Title
Intelligent Systems Reference Library
Series Volume
72
Copyright
2015
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-10247-4
DOI
10.1007/978-3-319-10247-4
Hardcover ISBN
978-3-319-10246-7
Softcover ISBN
978-3-319-37731-5
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XV, 320
Number of Illustrations
41 b/w illustrations
Topics