Advances in Data Analysis: Proceedings of the 30th Annual by Reinhold Decker

By Reinhold Decker

This booklet makes a speciality of exploratory info research, studying of latent constructions in datasets, and unscrambling of data. assurance information a vast diversity of equipment from multivariate records, clustering and type, visualization and scaling in addition to from info and time sequence research. It offers new methods for info retrieval and knowledge mining and stories a number of not easy functions in quite a few fields.

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Additional info for Advances in Data Analysis: Proceedings of the 30th Annual Conference of the Gesellschaft fur Klassifikation e.V., Freie Universitat Berlin, March ... Data Analysis, and Knowledge Organization)

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Therefore, AIC3 uses d = 3 as penalizing factor. The Average Weight of Evidence (AWE) criterion adds a third dimension to the information criteria described above. It weights fit, parsimony, and the performance of the classification (Banfield and Raftery (1993)). This measure uses the so-called classification log-likelihood (log Lc ) and is defined as AW E = −2 log Lc + 2NS ( 23 + log n). Apart from the five information criteria reported above, we also investigated a modified definition of the BIC, CAIC and AWE.

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