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This function predicts values based upon a model trained by rpc.
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'.
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))
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))
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))
options("utiml.seed", NA)
An object of type mlresult, based on the parameter probability.
Binary Relevance (BR)
# NOT RUN { model <- rpc(toyml, "RANDOM") pred <- predict(model, toyml) # } # NOT RUN { # }
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