Titlebook: Data Analysis; Scientific Modeling Wolfgang Gaul,Otto Opitz,Martin Schader Book 2000 Springer-Verlag Berlin · Heidelberg 2000 Optimization

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Classification and Clustering of Objects With VariantsThe method of . has proved a powerful method for reducing the error rate in Bayesian pattern recognition. The method serves to recover from ambiguities often not avoidable during the early stage of processing. Applications of this method to object identification, supervised classification, and clustering are discussed.

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From Data Mining to Knowledge Mining: An Introduction to Symbolic Data AnalysisThe need to extend standard data analysis methods (exploratory, clustering, factorial analysis, discrimination,…) to more complex data table is increasing in order to get more accurate information and summarize extensive data sets contained in huge databases. We define . (SDA) as the extension of standard Data Mining to such data tables.

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