Data Preprocessing in Data Mining

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Sprache: Englisch

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Beschreibung

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 [...] 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.

Zusammenfassung

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

Inhaltsverzeichnis

Introduction.- Data Sets and Proper Statistical Analysis of Data Mining Techniques.- Data Preparation Basic Models.- Dealing with Missing Values.- Dealing with Noisy Data.- Data Reduction.- Feature Selection.- Instance Selection.- Discretization.- A Data Mining Software Package Including Data Preparation and Reduction: KEEL.

Details

Erscheinungsjahr:	2014
Fachbereich:	Technik allgemein
Genre:	Mathematik , Medizin , Naturwissenschaften , Technik
Rubrik:	Naturwissenschaften & Technik
Medium:	Buch
Inhalt:	xv 320 S. 41 s/w Illustr. 320 p. 41 illus.
ISBN-13:	9783319102467
ISBN-10:	331910246X
Sprache:	Englisch
Herstellernummer:	86280296
Einband:	Gebunden
Autor:	García, Salvador Herrera, Francisco Luengo, Julián
Hersteller:	Springer International Publishing
Verantwortliche Person für die EU:	Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße:	241 x 160 x 24 mm
Von/Mit:	Salvador García (u. a.)
Erscheinungsdatum:	11.09.2014
Gewicht:	0,67 kg