Select Parameters for Tree
A utility function for use with the control argument of tree.
tree.control(nobs, mincut = 5, minsize = 10, mindev = 0.01)
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.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.
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.
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.
B. D. Ripley
Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.
tree
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