Returns a vector of predicted responses from a fitted tree object.
# S3 method for tree
predict(object, newdata = list(),
type = c("vector", "tree", "class", "where"),
split = FALSE, nwts, eps = 1e-3, ...)
fitted model object of class tree
. This is assumed to be the result
of some function that produces an object with the same named
components as that returned by the tree
function.
data frame containing the values at which predictions are required.
The predictors referred to in the right side
of formula(object)
must be present by name in newdata
.
If missing, fitted values are returned.
character string denoting whether the predictions are returned as a vector (default) or as a tree object.
governs the handling of missing values. If false, cases with missing
values are dropped down the tree until a leaf is reached or a node
for which the attribute is missing, and that node is used for
prediction. If split = TRUE
cases with missing attributes are
split into fractional cases and dropped down each side of the split.
The predicted values are averaged over the fractions to give the
prediction.
weights for the newdata
cases, used when predicting a tree.
a lower bound for the probabilities, used if events of predicted
probability zero occur in newdata
when predicting a tree.
further arguments passed to or from other methods.
If type = "vector"
:
vector of predicted responses or, if the response is a factor, matrix
of predicted class probabilities. This new object is obtained by
dropping newdata
down object
. For factor predictors, if an
observation contains a level not used to grow the tree, it is left at
the deepest possible node and frame$yval
or frame$yprob
at that
node is the prediction.
If type = "tree"
:
an object of class "tree"
is returned with new values
for frame$n
and frame$dev
. If
newdata
does not contain a column for the response in the formula
the value of frame$dev
will be NA
, and if some values in the
response are missing, the some of the deviances will be NA
.
If type = "class"
:
for a classification tree, a factor of the predicted classes (that
with highest posterior probability, with ties split randomly).
If type = "where"
:
the nodes the cases reach.
This function is a method for the generic function
predict()
for class tree
.
It can be invoked by calling predict(x)
for an
object x
of the appropriate class, or directly by
calling predict.tree(x)
regardless of the
class of the object.
Ripley, B. D. (1996). Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge. Chapter 7.
# NOT RUN {
data(shuttle, package="MASS")
shuttle.tr <- tree(use ~ ., shuttle, subset=1:253,
mindev=1e-6, minsize=2)
shuttle.tr
shuttle1 <- shuttle[254:256, ] # 3 missing cases
predict(shuttle.tr, shuttle1)
# }
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