Regression trees represent one of the most popular tools in predictive data mining applications. However, their performances severely degrade in the presence of highly-skewed and/or long-tailed error distributions, and especially for grossly mis-measured values of the dependent variable. In this paper, these issues are discussed from both a theoretical and a practical point of view, and some recent proposals to overcome these difficulties are presented.

Some issues on robustness of regression trees / G. Galimberti; M. Pillati; G. Soffritti. - STAMPA. - (2009), pp. 147-150. (Intervento presentato al convegno 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society tenutosi a Catania, Italy nel 9-11 Settembre 2009).

Some issues on robustness of regression trees

GALIMBERTI, GIULIANO;PILLATI, MARILENA;SOFFRITTI, GABRIELE
2009

Abstract

Regression trees represent one of the most popular tools in predictive data mining applications. However, their performances severely degrade in the presence of highly-skewed and/or long-tailed error distributions, and especially for grossly mis-measured values of the dependent variable. In this paper, these issues are discussed from both a theoretical and a practical point of view, and some recent proposals to overcome these difficulties are presented.
2009
Classification and Data Analysis 2009
147
150
Some issues on robustness of regression trees / G. Galimberti; M. Pillati; G. Soffritti. - STAMPA. - (2009), pp. 147-150. (Intervento presentato al convegno 7° Meeting of the Classification and Data Analysis Group of the Italian Statistical Society tenutosi a Catania, Italy nel 9-11 Settembre 2009).
G. Galimberti; M. Pillati; G. Soffritti
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/84936
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