| minsplit |
the minimum number of observations that must exist in a node for
a split to be attempted.
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| minbucket |
the minimum number of observations in any terminal <leaf> node.
If only one of minbucket or minsplit is specified,
the code either sets minsplit to minbucket*3 or
minbucket to minsplit/3, as appropriate.
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| cp |
the 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 at each step. The main role of this parameter is to save
computing time by pruning off splits that are obviously not worthwhile.
Essentially, the user informs the program that any split that does not improve
the fit by cp is likely pruned off by cross-validation, and
that hence the program need not pursue it.
If cp is given a positive value, mindev is set to -1.0.
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| mindev |
the split is limited on risk instead of complexity.
A node with risk less than mindev is not split.
Only one of mindev and cp is used.
If mindev is given a positive value, cp is set to -1.0.
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| maxcompete |
the number of competitor splits retained in the output. It is useful to
both which split was chosen and which variable came in second,
third, and so on.
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| maxsurrogate |
the number of surrogate splits retained in the output. If this value is set
to zero the computational time is shortened, because approximately half of the
computational time (other than setup) is used in the search for surrogate
splits.
|
| usesurrogate |
specifies how to use surrogates in the splitting process.
- 0 specifies display only. An observation with a missing value for
the primary split rule is not sent further down the tree.
A value of 0 corresponds to the action of tree.
- 1 specifies to use surrogates, in order, to split subjects
missing the primary variable. If all sorrogates are missing, the observation is not split.
- 2 specifies, if all surrogates are missing, to send the
observation in the majority direction. A value of 2 is the
recommendation of Breiman, et.al.
|
| xval |
an integer number representing the size of the cross-validation groups or
a vector of numbers to indicate in which group each observation belongs.
|
| surrogatestyle |
controls the selection of a best surrogate.
- If set to 0 (the 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 the surrogate.
The first option more severely penalizes covariates with a large number of
missing values.
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| maxdepth |
Set the maximum depth of any node of the final tree, with the root node counted
as depth 0 (if set past 30, arbor returns nonsense results).
|