tree.impurity: Internal Function that Determines the Impurity of a Subtree

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

Determines the impurity of a subtree.

Usage

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  tree.impurity(
	yprob, 
	number.of.observations.at.leaves, 
	leaf.classes, 
	impurity.measure = c("deviance","misclass"))

Arguments

yprob

A matrix of predicted class probabilities of leaves of the subtree considered in order of tree-growth (left to right).

number.of.observations.at.leaves

A vector denoting the number of observations at each of these leaves.

leaf.classes

A vector denoting the classes associated to these leaves.

impurity.measure

Character string denoting the measure of node heterogeneity to be used to guide cost-complexity pruning/trimming.

Details

R_α(T) = R(T) + α size(T)

When pruning and trimming trees, R(T) must be evaluated. Extracted arguments from oblique.tree objects is easiest.

Value

The impurity of the subtree.

Author(s)

A. Truong

References

Ripley, B. D. (1996). Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge. Chapter 7.

See Also

oblique.tree.

Examples

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#grow a tree on the Pima Indian dataset
data(Pima.tr, package = "MASS")
ob.tree <- oblique.tree(formula		= type~.,
			data		= Pima.tr,
			oblique.splits	= "on")

#deviance of entire tree
subtree.leaves <- ob.tree$frame$var == "<leaf>"
oblique.tree:::tree.impurity(	
	yprob 					= ob.tree$frame$yprob[subtree.leaves,,drop=FALSE],
	number.of.observations.at.leaves 	= ob.tree$frame$n[subtree.leaves],
	leaf.classes 				= ob.tree$frame$yval[subtree.leaves],
	impurity.measure 			= "deviance")

oblique.tree documentation built on April 15, 2017, 4:38 a.m.