MachineShop (version 3.5.0)

AdaBagModel: Bagging with Classification Trees

Description

Fits the Bagging algorithm proposed by Breiman in 1996 using classification trees as single classifiers.

Usage

AdaBagModel(
  mfinal = 100,
  minsplit = 20,
  minbucket = round(minsplit/3),
  cp = 0.01,
  maxcompete = 4,
  maxsurrogate = 5,
  usesurrogate = 2,
  xval = 10,
  surrogatestyle = 0,
  maxdepth = 30
)

Value

MLModel class object.

Arguments

mfinal

number of trees to use.

minsplit

minimum number of observations that must exist in a node in order for a split to be attempted.

minbucket

minimum number of observations in any terminal node.

cp

complexity parameter.

maxcompete

number of competitor splits retained in the output.

maxsurrogate

number of surrogate splits retained in the output.

usesurrogate

how to use surrogates in the splitting process.

xval

number of cross-validations.

surrogatestyle

controls the selection of a best surrogate.

maxdepth

maximum depth of any node of the final tree, with the root node counted as depth 0.

Details

Response types:

factor

Automatic tuning of grid parameters:

mfinal, maxdepth

Further model details can be found in the source link below.

See Also

bagging, fit, resample

Examples

# \donttest{
## Requires prior installation of suggested package adabag to run

fit(Species ~ ., data = iris, model = AdaBagModel(mfinal = 5))
# }