predict.BRmodel: Predict Method for Binary Relevance

In utiml: Utilities for Multi-Label Learning

Description

This function predicts values based upon a model trained by br.

Usage

## S3 method for class 'BRmodel'
predict(
  object,
  newdata,
  probability = getOption("utiml.use.probs", TRUE),
  ...,
  cores = getOption("utiml.cores", 1),
  seed = getOption("utiml.seed", NA)
)

Arguments

object	Object of class 'BRmodel'.
newdata	An object containing the new input data. This must be a matrix, data.frame or a mldr object.
probability	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.
cores	The number of cores to parallelize the training. Values higher than 1 require the parallel package. (Default: options("utiml.cores", 1))
seed	An optional integer used to set the seed. This is useful when the method is run in parallel. (Default: options("utiml.seed", NA))

Value

An object of type mlresult, based on the parameter probability.

See Also

Binary Relevance (BR)

Examples

model <- br(toyml, "RANDOM")
pred <- predict(model, toyml)


# Predict SVM scores
model <- br(toyml, "SVM")
pred <- predict(model, toyml)

# Predict SVM bipartitions running in 2 cores
pred <- predict(model, toyml, probability = FALSE, CORES = 2)

# Passing a specif parameter for SVM predict algorithm
pred <- predict(model, toyml, na.action = na.fail)

utiml documentation built on May 31, 2021, 9:09 a.m.