Algorithms from and for Nature and Life [electronic resource] : Classification and Data Analysis / edited by Berthold Lausen, Dirk Van den Poel, Alfred Ultsch.
By: Lausen, Berthold [editor.].
Contributor(s): Van den Poel, Dirk [editor.] | Ultsch, Alfred [editor.] | SpringerLink (Online service).
Material type: BookSeries: Studies in Classification, Data Analysis, and Knowledge Organization: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2013Description: XX, 547 p. 111 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319000350.Subject(s): Statistics | Data mining | Social sciences -- Data processing | Mathematical statistics | Economics -- Statistics | Operations research | Statistics | Statistics and Computing/Statistics Programs | Computer Appl. in Social and Behavioral Sciences | Operation Research/Decision Theory | Operations Research, Management Science | Data Mining and Knowledge Discovery | Statistics for Business/Economics/Mathematical Finance/InsuranceDDC classification: 519.5 Online resources: Click here to access onlineInvited -- Clustering and Unsupervised Learning -- Statistical Data Analysis, Visualization and Scaling -- Bioinformatics and Biostatistics -- Archaeology and Geography, Psychology and Educational Sciences -- Text Mining, Social Networks and Clustering -- Banking and Finance -- Marketing and Management -- Music Classification Workshop.
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operations research, and statistics. In addition to theory-oriented contributions various application areas are included. Moreover, traditional classification research directions concerning network data, graphs, and social relationships as well as statistical musicology describe examples for current interest fields tackled by the authors. The book comprises a total of 55 selected papers presented at the Joint Conference of the German Classification Society (GfKl), the German Association for Pattern Recognition (DAGM), and the Symposium of the International Federation of Classification Societies (IFCS) in 2011.
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