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Challenges at the Interface of Data Analysis, Computer Science, and Optimization: Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010 2012 [Pehme köide]

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  • Formaat: Paperback / softback, 598 pages, kõrgus x laius: 235x155 mm, kaal: 926 g, 163 Illustrations, black and white; XIV, 598 p. 163 illus., 1 Paperback / softback
  • Sari: Studies in Classification, Data Analysis, and Knowledge Organization
  • Ilmumisaeg: 09-Feb-2012
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642244653
  • ISBN-13: 9783642244650
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Challenges at the Interface of Data Analysis, Computer Science, and Optimization: Proceedings of the 34th Annual Conference of the Gesellschaft für Klassifikation e. V., Karlsruhe, July 21 - 23, 2010 2012Suurem pilt
  • Formaat: Paperback / softback, 598 pages, kõrgus x laius: 235x155 mm, kaal: 926 g, 163 Illustrations, black and white; XIV, 598 p. 163 illus., 1 Paperback / softback
  • Sari: Studies in Classification, Data Analysis, and Knowledge Organization
  • Ilmumisaeg: 09-Feb-2012
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642244653
  • ISBN-13: 9783642244650
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783642244650.html
Märksõnad:
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.

Classification, Cluster Analysis, and Multidimensional Scaling.- Quantification Theory.- Analysis of m-Mode n-Way and Asymmetric Data.- Analysis of Visual, Spatial, and Temporal Data.- Network Data, Graphs, and Social Relationships.- Text Mining.- Dimension Reduction.- Statistical Musicology.- Data Analysis in Banking and Finance.- Data Analysis in Health and Environment.- Analysis of Marketing, Conjoint, and Multigroup Data.- Data Analysis in Education and Psychology.- Analysis of Tourism Data.