powered by
Fit an rpart model.
rpart
RPartModel( minsplit = 20, minbucket = round(minsplit/3), cp = 0.01, maxcompete = 4, maxsurrogate = 5, usesurrogate = 2, xval = 10, surrogatestyle = 0, maxdepth = 30 )
MLModel class object.
MLModel
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, numeric, Surv
factor
numeric
Surv
cp
Further model details can be found in the source link below.
rpart, fit, resample
fit
resample
# \donttest{ ## Requires prior installation of suggested packages rpart and partykit to run fit(Species ~ ., data = iris, model = RPartModel) # }
Run the code above in your browser using DataLab