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Data Science, Learning by Latent Structures, and Knowledge Discovery : Springer Nature Proceedings excluding Computer Science - Berthold Lausen

Data Science, Learning by Latent Structures, and Knowledge Discovery

By: Berthold Lausen (Editor), Sabine Krolak-Schwerdt (Editor), Matthias Böhmer (Editor)

eText | 6 May 2015

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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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Non-FictionMathematicsProbability & StatisticsBusiness & ManagementOperational ResearchSales & MarketingComputing & I.T.DatabasesData MiningScienceBiology, Life SciencesPsychology
Psychological MethodologyPsychological Testing & MeasurementMedicineMedicine in GeneralPublic Health & Preventive MedicineEpidemiology & Medical StatisticsManagement & Management TechniquesManagement Decision Making

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