rpart trees.rpart object.
Of these, only the where component has the same length as
the data used to fit the rpart object.
row.names of frame contain the (unique) node numbers that
follow a binary ordering indexed by node depth.
Elements of frame include var,
the variable used in the split at each node
(leaf nodes are denoted by the string n, the size of each node,
dev, the deviance of each node,
yval, the fitted value of the response at each node,
and splits, a two column matrix of left and right split labels
for each node.
All of these are the same as for an rpart object.
Extra response information is in yval2, which contains the number of
events at the node (poisson), or a matrix containing the vector of
class counts for each node (classification).
Also included in the frame are complexity, the complexity parameter at
which this split will collapse, ncompete, the number of competitor splits
retained, and 'nsurrogate', the number of surrogate splits retained.
}
frame corresponding to the leaf node
that each observation falls into.
}
count, the number of observations sent left
or right by the split (for competitor splits this is the number that
would have been sent left or right had this split been used, for surrogate
splits it is the number missing the primary split variable which were decided
using this surrogate), ncat, the number of categories or levels for the
variable (+-1 for a continuous variable), improve, which is the improvement
in deviance given by this split, or, for surrogates, the concordance of the
surrogate with the primary, and split, the numeric split point. For
a factor, this column contains the row number of the csplit matrix.
For a continuous variable, the sign of ncat determines whether the
subset xexpression and class term summarizing the formula.
Used by various methods, but typically not of direct relevance to users.
}
update(tree).
Optional components include the matrix of predictors (x) and the
response variable (y) used to construct the rpart object.
}
rpart, tree.object.