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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
Statistics, general
Marketing
Psychometrics
Biostatistics
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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