Tree Predictions
Compute predictions from party objects.
## S3 method for class 'party'
predict(object, newdata = NULL, perm = NULL, ...)
predict_party(party, id, newdata = NULL, ...)
## Default S3 method:
predict_party(party, id, newdata = NULL, FUN = NULL, ...)
## S3 method for class 'constparty'
predict_party(party, id, newdata = NULL,
type = c("response", "prob", "quantile", "density", "node"),
at = if (type == "quantile") c(0.1, 0.5, 0.9),
FUN = NULL, simplify = TRUE, ...)
## S3 method for class 'simpleparty'
predict_party(party, id, newdata = NULL,
type = c("response", "prob", "node"), ...)object |
objects of class |
newdata |
an optional data frame in which to look for variables with which to predict, if omitted, the fitted values are used. |
perm |
an optional character vector of variable names. Splits of
nodes with a primary split in any of these variables will
be permuted (after dealing with surrogates). Note that
surrogate split in the |
party |
objects of class |
id |
a vector of terminal node identifiers. |
type |
a character string denoting the type of predicted value
returned, ignored when argument |
FUN |
a function to extract ( |
at |
if the return value is a function (as the empirical cumulative distribution
function or the empirical quantile function), this function is evaluated
at values |
simplify |
a logical indicating whether the resulting list of predictions should be converted to a suitable vector or matrix (if possible). |
... |
additional arguments. |
The predict method for party objects
computes the identifiers of the predicted terminal nodes, either
for new data in newdata or for the learning samples
(only possible for objects of class constparty).
These identifiers are delegated to the corresponding
predict_party method which computes (via
FUN for class constparty)
or extracts (class simpleparty) the actual predictions.
A list of predictions, possibly simplified to a numeric vector, numeric matrix or factor.
## fit tree using rpart
library("rpart")
rp <- rpart(skips ~ Opening + Solder + Mask + PadType + Panel,
data = solder, method = 'anova')
## coerce to `constparty'
pr <- as.party(rp)
## mean predictions
predict(pr, newdata = solder[c(3, 541, 640),])
## ecdf
predict(pr, newdata = solder[c(3, 541, 640),], type = "prob")
## terminal node identifiers
predict(pr, newdata = solder[c(3, 541, 640),], type = "node")
## median predictions
predict(pr, newdata = solder[c(3, 541, 640),],
FUN = function(y, w = 1) median(y))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.