Within the framework of recursive partitioning algorithms by tree-based methods, this paper provides a contribution on both the visual representation of the final data partition in a geometrical space and the selection of the decision tree. The results in terms of error rate are really similar to the ones returned by the Classification And Regression Trees procedure, showing how this novel way to select the best tree is a valid alternative to the well know cost-complexity pruning.
Visual model representation and selection for classification and regression trees / Iorio, Carmela; Aria, Massimo; D'Ambrosio, Antonio. - ELETTRONICO. - (2013), pp. 276-279. (Intervento presentato al convegno 9th Meeting of the Classification and Data Analysis Group tenutosi a Modena nel 18-20 September 2013).
Visual model representation and selection for classification and regression trees
IORIO, CARMELA;ARIA, MASSIMO;D'AMBROSIO, ANTONIO
2013
Abstract
Within the framework of recursive partitioning algorithms by tree-based methods, this paper provides a contribution on both the visual representation of the final data partition in a geometrical space and the selection of the decision tree. The results in terms of error rate are really similar to the ones returned by the Classification And Regression Trees procedure, showing how this novel way to select the best tree is a valid alternative to the well know cost-complexity pruning.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
