plot.itree {itree} | R Documentation |
Plots an itree
object on the current graphics device. This is
based on the plotting function from rpart but modifies/extends
it in various ways to deal with some of itree
's capabilities.
## S3 method for class 'itree' plot(x, uniform=FALSE, branch=1, compress=FALSE, nspace, margin=0, minbranch=.3, highlight.color="black",do_node_re=FALSE, ...)
x |
a fitted object of class |
uniform |
if |
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. |
compress |
if |
nspace |
the amount of extra space between a node with children and
a leaf, as compared to the minimal space between leaves.
Applies to compressed trees only. The default is the value of
|
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). |
minbranch |
set the minimum length for a branch to |
highlight.color |
If the |
do_node_re |
Set to |
... |
arguments to be passed to or from other methods. |
This function is a method for the generic function plot
, for objects
of class itree
. The y-coordinate of the top node of the tree will always be 1.
The coordinates of the nodes are returned as a list, with
components x
and y
.
An unlabeled plot is produced on the current graphics device.
#the rpart example: fit <- itree(Price ~ Mileage + Type + Country, cu.summary) plot(fit, compress=TRUE) text(fit, use.n=TRUE) ### new to itree, plotting node risk: require(mlbench); data(BostonHousing) #fit a tree: cart <- itree(medv~.,BostonHousing,minsplit=25,minbucket=25,cp=0) #generate theta-hat values by computing average out-of-bag loss: ## Not run: theta_hats <- getOOBLoss(model_tree.obj=cart.bh,data=bh,nboot=100) # Then for each leaf we estimate local risk by the mean in-node theta-hat. lre <- estNodeRisk(tree.obj=cart.bh,est_observation_loss=theta_hats$avgOOBloss) # to add the lre to the plot: plot(cart.bh, do_node_re= TRUE, uniform=TRUE) text(cart.bh, est_node_risk = lre) ## End(Not run) #plot using highlighting for one-sided methods: purity.tree <- itree(medv~.,BostonHousing,minsplit=25,minbucket=25,cp=0,method="purity") plot(purity.tree,highlight.color="blue") text(purity.tree)