rpart
object
prettyTree(t, compress = F, branch = 0.2, margin = 0.1, uniform = T, all = T, cex = 0.8, font = 10, use.n = T, fwidth = 0.5, fheight = 0.45, center = 0, ...)
rpart
object
plot.rpart()
. See the help page of
this function for further details. Defaults to F.
plot.rpart()
. See the help page of
this function for further details. Defaults to 0.2.
plot.rpart()
. See the help page of
this function for further details. Defaults to 0.1.plot.rpart()
. See the help page of
this function for further details. Defaults to T.text.rpart()
. See the help page of
this function for further details. Defaults to T.text.rpart()
. See the help page of
this function for further details. Defaults to T.text.rpart()
. See the help page of
this function for further details. Defaults to 0.5.text.rpart()
. See the help page of
this function for further details. Defaults to 0.45.plot.rpart()
and text.rpart()
plot()
and then the function text()
to a
rpart
object: it essentially obtains a graphical representation
of a tree-based model. The basic differences are related to visual
formatting of the trees.
Torgo, L. (2010) Data Mining using R: learning with case studies, CRC Press (ISBN: 9781439810187).
plot.rpart
, text.rpart
,
rpartXse
, rpart
data(iris)
tree <- rpartXse(Species ~ ., iris)
## Not run:
# prettyTree(tree)
# prettyTree(tree,all=F,use.n=F,branch=0)
# ## End(Not run)
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