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Title Data dcience, learning by latent structures, and knowledge discovery / edited by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Bohmer
Imprint Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015
book jacket
Descript 1 online resource (xxii, 560 pages) : illustrations (some color), digital ; 24 cm
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Series Studies in classification, data analysis, and knowledge organization, 1431-8814
Studies in classification, data analysis, and knowledge organization
Note 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
Host Item Springer eBooks
Subject Mathematical statistics
Data mining
Statistics, general
Data Mining and Knowledge Discovery
Operation Research/Decision Theory
Alt Author Lausen, Berthold, editor
Krolak-Schwerdt, Sabine, editor
Bohmer, Matthias, editor
SpringerLink (Online service)
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