Growing a tree classifier with imprecise data

Symbolic data analysis proposes a general framework to extend usual data analysis methods to more complex data called symbolic objects. The prediction problem for symbolic objects is defined: it is seen to be a generalization of the prediction for standard data. An algorithm of tree-growing is devel...

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Veröffentlicht in:	Pattern recognition letters 2000-08, Vol.21 (9), p.787-803
Hauptverfasser:	Ciampi, A., Diday, E., Lebbe, J., Périnel, E., Vignes, R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification tree Probabilistically imprecise data Supervised learning Symbolic data analysis “Soft” recursive partition
Online-Zugang:	Volltext
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