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Data dcience, learning by latent str...

Bohmer, Matthias.

Data dcience, learning by latent structures, and knowledge discovery

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data dcience, learning by latent structures, and knowledge discoveryedited by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Bohmer.
other author:	Lausen, Berthold.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg :2015.
Description:	xxii, 560 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematical statistics.
Online resource:	http://dx.doi.org/10.1007/978-3-662-44983-7
ISBN:	9783662449837 (electronic bk.)

Data dcience, learning by latent structures, and knowledge discovery
Data dcience, learning by latent structures, and knowledge discovery[electronic resource] /edited by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Bohmer. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xxii, 560 p. :ill. (some col.), digital ;24 cm. - Studies in classification, data analysis, and knowledge organization,1431-8814. - Studies in classification, data analysis, and knowledge organization..

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking, and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics, and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.

ISBN: 9783662449837 (electronic bk.)

Standard No.: 10.1007/978-3-662-44983-7doiSubjects--Topical Terms:

181877
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Data dcience, learning by latent structures, and knowledge discovery
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245 0 0 $a Data dcience, learning by latent structures, and knowledge discovery $h [electronic resource] / $c edited by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Bohmer.
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300 $a xxii, 560 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in classification, data analysis, and knowledge organization, $x 1431-8814
520 $a This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering, and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking, and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics, and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
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700 1 $a Lausen, Berthold. $3 725108
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