tree.control: Select Parameters for Tree

In tree: Classification and Regression Trees

Select Parameters for Tree

Description

A utility function for use with the control argument of tree.

Usage

tree.control(nobs, mincut = 5, minsize = 10, mindev = 0.01)

Arguments

nobs	The number of observations in the training set.
mincut	The minimum number of observations to include in either child node. This is a weighted quantity; the observational weights are used to compute the ‘number’. The default is 5.
minsize	The smallest allowed node size: a weighted quantity. The default is 10.
mindev	The within-node deviance must be at least this times that of the root node for the node to be split.

Details

This function produces default values of mincut and minsize, and ensures that mincut is at most half minsize.

To produce a tree that fits the data perfectly, set mindev = 0 and minsize = 2, if the limit on tree depth allows such a tree.

Value

A list:

mincut	The maximum of the input or default mincut and 1
minsize	The maximum of the input or default minsize and 2.
nmax	A estimate of the maximum number of nodes that might be grown.
nobs	The input nobs.

Note

The interpretation of mindev given here is that of Chambers and Hastie (1992, p. 415), and apparently not what is actually implemented in S. It seems S uses an absolute bound.

Author(s)

B. D. Ripley

References

Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.

See Also

tree

tree documentation built on Feb. 16, 2023, 10:10 p.m.