node_imptree {imptree} | R Documentation |
Access probability information of nodes
node_imptree(x, idx = NULL) ## S3 method for class 'node_imptree' print(x, ...)
x |
An object of class |
idx |
numeric or integer vector of indices specifying
the sequential node access from the root node.
Numeric values are coerced to integer as
by |
... |
Further arguments passed to |
This function acceses the properties of a specific node
of an imprecise tree.
An existence check on the stored C++ object reference is
carried out at first. If the reference is not valid the
original call for "x"
is printed as error.
An object of class node_imptree
containing
information on the properties of the node as a list:
probint |
matrix containing the bounds of the imprecise probability distribution and the absolute observed frequencies of the classification variable within the node. |
depth |
The depth of the node with the tree. |
splitter |
The name of the variable used for splitting
as character; |
children |
The number of children of the node. |
traindataIdx |
Vector giving the indexes of the training data contained within the node |
ipmodel |
List giving details about the used imprecise probability model to obatin the credal set:
|
The printing function returns the
node_imptree
object invisibly.
Paul Fink Paul.Fink@stat.uni-muenchen.de
imptree
, for global information on
the generated tree summary.imptree
data("carEvaluation") ## create a tree with IDM (s=1) to full size ## carEvaluation, leaving the first 10 observations out ip <- imptree(acceptance~., data = carEvaluation[-(1:10),], method="IDM", method.param = list(splitmetric = "globalmax", s = 1), control = list(depth = NULL, minbucket = 1)) ## obtain information on the root node node_imptree(x = ip, idx = NULL) ## obtain information on the 2nd note in the 1st level node_imptree(x = ip, idx = c(1, 2)) ## reference to an invalid index and/or level generates error ## Not run: node_imptree(x = ip, idx = c(1,10)) # no 10th node on 1st level ## End(Not run)