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. The conditional impurity in the definition of splitting criterion is defined as a classical impurity measure weighted by a predictability index.
Conditional classification trees by weighting the Gini impurity measure / D'Ambrosio, Antonio; Tutore, V. A.. - STAMPA. - (2011), pp. 273-280. [10.1007/978-3-642-11363-5_31]
Conditional classification trees by weighting the Gini impurity measure
D'AMBROSIO, ANTONIO;
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. The conditional impurity in the definition of splitting criterion is defined as a classical impurity measure weighted by a predictability index.File in questo prodotto:
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