This function predicts values based upon a model trained by
rpc
.
# S3 method for RPCmodel
predict(object, newdata,
probability = getOption("utiml.use.probs", TRUE), ...,
cores = getOption("utiml.cores", 1), seed = getOption("utiml.seed", NA))
Object of class 'RPCmodel
'.
An object containing the new input data. This must be a matrix, data.frame or a mldr object.
Logical indicating whether class probabilities should be
returned. (Default: getOption("utiml.use.probs", TRUE)
)
Others arguments passed to the base algorithm prediction for all subproblems.
The number of cores to parallelize the training. Values higher
than 1 require the parallel package. (Default:
options("utiml.cores", 1)
)
An optional integer used to set the seed. This is useful when
the method is run in parallel. (Default: options("utiml.seed", NA)
)
An object of type mlresult, based on the parameter probability.
# NOT RUN {
model <- rpc(toyml, "RANDOM")
pred <- predict(model, toyml)
# }
# NOT RUN {
# }
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