fdm2id: cartplot – R documentation

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cartplot

CART Plot

Plot a decision tree obtained by CART.

cartplot(
  model,
  margin = 0.2,
  branch = 0.3,
  uniform = TRUE,
  fancy = TRUE,
  pretty = TRUE,
  fwidth = 0,
  fheight = 0,
  ...
)

`model`	The decision tree.
`margin`	an extra fraction of white space to leave around the borders of the tree. (Long labels sometimes get cut off by the default computation).
`branch`	controls the shape of the branches from parent to child node. Any number from 0 to 1 is allowed. A value of 1 gives square shouldered branches, a value of 0 give V shaped branches, with other values being intermediate.
`uniform`	if `TRUE`, uniform vertical spacing of the nodes is used; this may be less cluttered when fitting a large plot onto a page. The default is to use a non-uniform spacing proportional to the error in the fit.
`fancy`	Logical. If `TRUE`, nodes are represented by ellipses (interior nodes) and rectangles (leaves) and labeled by yval. The edges connecting the nodes are labeled by left and right splits.
`pretty`	an alternative to the minlength argument, see `labels.rpart`.
`fwidth`	Relates to option `fancy` and the width of the ellipses and rectangles. If `fwidth < 1` then it is a scaling factor (default = 0.8). If `fwidth > 1` then it represents the number of character widths (for current graphical device) to use.
`fheight`	Relates to option `fancy` and the width of the ellipses and rectangles. If `fwidth < 1` then it is a scaling factor (default = 0.8). If `fwidth > 1` then it represents the number of character heights (for current graphical device) to use.
`...`	Other parameters.

require (datasets)
data (iris)
model = CART (iris [, -5], iris [, 5])
cartplot (model)

Data Mining and R Programming for Beginners

v0.9.5

GPL-3

Authors

Alexandre Blansché [aut, cre]

Initial release