Overview
- 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
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 72)
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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.
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Keywords
Table of contents (10 chapters)
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Front Matter
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Back Matter
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)Authors and Affiliations
Bibliographic Information
Book Title: Data Preprocessing in Data Mining
Authors: Salvador García, Julián Luengo, Francisco Herrera
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-10247-4
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Hardcover ISBN: 978-3-319-10246-7Published: 11 September 2014
Softcover ISBN: 978-3-319-37731-5Published: 10 September 2016
eBook ISBN: 978-3-319-10247-4Published: 30 August 2014
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XV, 320
Number of Illustrations: 41 b/w illustrations
Topics: Computational Intelligence, Image Processing and Computer Vision, Data Mining and Knowledge Discovery