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Data Preprocessing in Data Mining

Intelligent Systems Reference Library

Book 72

Salvador GarcíaJulián LuengoFrancisco HerreraAugust 30, 2014

Springer

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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Additional Information

Publisher

Springer

Published on

Aug 30, 2014

Pages

320

ISBN

9783319102474

Features

Flowing text, Original pages

Best For

Web, Tablet, Phone, eReader

Language

English

Genres

Computers / Computer Graphics

Computers / Databases / Data Mining

Computers / Intelligence (AI) & Semantics

Computers / Optical Data Processing

Technology & Engineering / General

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