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Titlebook: Between Data Science and Applied Data Analysis; Proceedings of the 2 Martin Schader,Wolfgang Gaul,Maurizio Vichi Conference proceedings 200

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Intelligent Transportation Systems this strategy allows not only to obtain a smooth nonparametric estimate of the regression surface, but also to automatically determine the model complexity and to perform a covariate selection. The performances of the proposed strategy are evaluated on simulated data sets.
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Methods to Combine Classification Treescted by means of cross-validation or bootstrap samples, or obtained from independent data sets having the same predictors and class variables. An example of application of the proposed procedure to a real data set is then illustrated and discussed.
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Multivariate Mixture Models Estimation: A Genetic Algorithm Approachumber of mixture components is unknown is investigated and some estimation procedures are suggested. Real data examples and simulated data sets are used to illustrate the merits of the proposed procedure and for comparison purpose.
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Robust Classification Through the Forward Searcht on the classification of other units. We use plots of the Mahalanobis distances of the individual observations during the search to obtain our classification. Normality of the data is important, so we present a multivariate form of the Box-Cox family of transformations, of course combined with the forward search.
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Some Issues on Clustering of Functional Datan a landmark description which takes into account the . of each function and suggest also a graph-like representation which can help in the classification process. The method is illustrated using a real data set based on precipitation records.
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