Usage
rpart.control(minsplit=20, minbucket=round(minsplit/3), cp=0.01,
maxcompete=4, maxsurrogate=5, usesurrogate=2, xval=10,
surrogatestyle=0, maxdepth=30, ...)Arguments
minsplit
the minimum number of observations that must exist in a node, in order for
a split to be attempted.
minbucket
the minimum number of observations in any terminal minbucket or minsplit is specified,
the code either sets minsplit to minbucket*3
or minbucket
cp
complexity parameter. Any split that does not decrease the overall
lack of fit by a factor of cp is not attempted. For instance,
with anova splitting, this means that the overall Rsquare must
increase by cp a
maxcompete
the number of competitor splits retained in the output. It is useful to
know not just which split was chosen, but which variable came in second,
third, etc.
maxsurrogate
the number of surrogate splits retained in the output. If this is set to
zero the compute time will be shortened, since approximately half of the
computational time (other than setup) is used in the search for surrogate
splits.
usesurrogate
how to use surrogates in the splitting process. 0= display only; an
observation with a missing value for the primary split rule is not sent
further down the tree. 1= use surrogates, in order, to split subjects
missing the primary variable; if all
xval
number of cross-validations
surrogatestyle
controls the selection of a best surrogate.
If set to 0 (default) the program uses the total number of correct
classification for a potential surrogate variable,
if set to 1 it uses the percent correct, calculated over the non-missing
values of th
maxdepth
Set the maximum depth of any node of the final tree, with the root
node counted as depth 0 (past 30 rpart will give nonsense results on
32-bit machines).
...
mop up other arguments.