This paper introduces the concept of the conditional impurity in the framework of tree-based models in order to deal with the analysis of three-way data, where a response variable and a set of predictors are measured on a sample of objects in different occasions.

Conditional classification trees by weighting the Gini Impurity measure

2011

Abstract

This paper introduces the concept of the conditional impurity in the framework of tree-based models in order to deal with the analysis of three-way data, where a response variable and a set of predictors are measured on a sample of objects in different occasions.
2011
Istituto di Ricerca su Innovazione e Servizi per lo Sviluppo - IRISS
New Perspectives in Statistical Modeling and Analysis. Studies in Classification, Data Analysis, and Knowledge Organization.
978-3-642-11362-8
Sì, ma tipo non specificato
Catania
Binary segmentation
Gini impurity
Three-way data
2
none
Antonio, D'Ambrosio; Tutore Valerio Aniello,
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/60566
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