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Data dcience, learning by latent str...
Data dcience, learning by latent structures, and knowledge discovery[electronic resource] /
纪录类型:
书目-电子资源 : Monograph/item
[NT 15000414] null:
519.5
[NT 47271] Title/Author:
Data dcience, learning by latent structures, and knowledge discovery/ edited by Berthold Lausen, Sabine Krolak-Schwerdt, Matthias Bohmer.
[NT 51406] other author:
出版者:
Berlin, Heidelberg : : Springer Berlin Heidelberg :, 2015.
面页册数:
xxii, 560 p. : : ill. (some col.), digital ;; 24 cm.
标题:
ISBN:
9783662449837 (electronic bk.)
ISBN:
9783662449820 (paper)
[NT 15000229] null:
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.#
Data dcience, learning by latent structures, and knowledge discovery[electronic resource] /
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.
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:
353965
LC Class. No.: QA276
Dewey Class. No.: 519.5
Data dcience, learning by latent structures, and knowledge discovery[electronic resource] /
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