A utility function for use with the control argument of tree.
tree.control(nobs, mincut = 5, minsize = 10, mindev = 0.01)The number of observations in the training set.
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.
The smallest allowed node size: a weighted quantity. The default is 10.
The within-node deviance must be at least this times that of the root node for the node to be split.
A list:
The maximum of the input or default mincut and 1
The maximum of the input or default minsize and 2.
A estimate of the maximum number of nodes that might be grown.
The input nobs.
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.
Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.