Fits the Bagging algorithm proposed by Breiman in 1996 using classification trees as single classifiers.
AdaBagModel(
mfinal = 100,
minsplit = 20,
minbucket = round(minsplit/3),
cp = 0.01,
maxcompete = 4,
maxsurrogate = 5,
usesurrogate = 2,
xval = 10,
surrogatestyle = 0,
maxdepth = 30
)MLModel class object.
number of trees to use.
minimum number of observations that must exist in a node in order for a split to be attempted.
minimum number of observations in any terminal node.
complexity parameter.
number of competitor splits retained in the output.
number of surrogate splits retained in the output.
how to use surrogates in the splitting process.
number of cross-validations.
controls the selection of a best surrogate.
maximum depth of any node of the final tree, with the root node counted as depth 0.
factor
mfinal, maxdepth
Further model details can be found in the source link below.
bagging, fit,
resample
# \donttest{
## Requires prior installation of suggested package adabag to run
fit(Species ~ ., data = iris, model = AdaBagModel(mfinal = 5))
# }
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