Titlebook: Data Science; Innovative Developme Francesco Palumbo,Angela Montanari,Maurizio Vichi Conference proceedings 2017 Springer International Pub

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Coexisting General Medical Diseaseste and methods for investigation. Commonly to many fields of research, these studies are frequently affected by incompleteness of information, a problem that, if not duly handled, may seriously invalidate conclusions drawn from investigations. Regarding cardiovascular risk assessment, coronary risk

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Danon Kaewkes,Robert Naami,Andrew Luxhojiance) and variability due to estimation (estimation variance). The estimation variance can be calculated by using the corresponding formula or, alternatively, it can be approximated by using bootstrap methodology. When we use bootstrap methodology we are able to obtain, in addition, the predictive

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Missing Data Imputation and Its Effect on the Accuracy of Classificationo particular significance in the fact that a particular observation has an attribute value missing. A common approach in coping with these missing values is to replace the missing value using some plausible value, and the resulting completed data set is analysed using standard methods. We evaluate t

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On Coupling Robust Estimation with Regularization for High-Dimensional Datay desirable, which are resistant to outliers. This work has the aim to propose new robust classification procedures for high-dimensional data and algorithms for their efficient computation. Particularly, we use the idea of implicit weights assigned to individual observation to propose several robust

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Classification Methods in the Research on the Financial Standing of Construction Enterprises After B, but few papers concern the statistical evaluation of financial standing of companies after they have been declared bankrupt. The examination of their way out from the insolvency problem may be a source of valuable information, useful for the assessment of the probability that other bankrupt enterp

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