Recursive Partitioning and Regression Trees Object
Description
These are objects representing fitted rpart
trees.
Value
frame 
data frame with one row for each node in the tree.
The Extra response information which may be present is in 
where 
an integer vector of the same length as the number of observations in the
root node, containing the row number of 
call 
an image of the call that produced the object, but with the arguments
all named and with the actual formula included as the formula argument.
To reevaluate the call, say 
terms 
an object of class 
splits 
a numeric matrix describing the splits: only present if there are any.
The row label is the name of
the split variable, and columns are 
csplit 
an integer matrix. (Only present only if at least one of the split
variables is a factor or ordered factor.) There is a row for
each such split, and the number of columns is the largest number of
levels in the factors. Which row is given by the 
method 
character string: the method used to grow the tree. One of

cptable 
a matrix of information on the optimal prunings based on a complexity parameter. 
variable.importance 
a named numeric vector giving the importance of each variable. (Only
present if there are any splits.) When printed by

numresp 
integer number of responses; the number of levels for a factor response. 
parms, control 
a record of the arguments supplied, which defaults filled in. 
functions 
the 
ordered 
a named logical vector recording for each variable if it was an ordered factor. 
na.action 
(where relevant) information returned by 
There may be attributes "xlevels"
and "levels"
recording the levels of any factor splitting variables and of a factor
response respectively.
Optional components include the model frame (model
), the matrix
of predictors (x
) and the response variable (y
) used to
construct the rpart
object.
Structure
The following components must be included in a legitimate rpart
object.
See Also
rpart
.