text.itree {itree} | R Documentation |
Labels the current plot of the tree dendrogram with text.
Extends text.rpart
to also print itree
's node risk estimate
along with the fitted values.
## S3 method for class 'itree' text(x, splits=TRUE, label, FUN=text, all=FALSE, pretty=NULL, digits=getOption("digits") - 3, use.n=FALSE, fancy=FALSE, fwidth=0.8, fheight=0.8, est_node_risk = NULL,use_sd=FALSE, ...)
x |
fitted model object of class |
splits |
logical flag. If |
label |
For compatibility with |
FUN |
the name of a labeling function, e.g. |
all |
Logical. If |
pretty |
an integer denoting the extent to which factor levels in split labels
will be abbreviated. A value of (0) signifies no abbreviation. A
|
digits |
number of significant digits to include in numerical labels. |
use.n |
Logical. If |
fancy |
Logical. If |
fwidth |
Relates to option |
fheight |
Relates to option |
est_node_risk |
If not |
use_sd |
If |
... |
Graphical parameters may also be supplied as arguments to this
function (see |
the current plot of a tree dendrogram is labeled.
text
, plot.itree
, itree
,
post.itree
, abbreviate
# from rpart: freen.tr <- itree(y ~ ., freeny) plot(freen.tr) text(freen.tr, use.n=TRUE, all=TRUE) ###unique 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: #don't run it because of time to do the bootstrap... 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)