Predict Method for Binary Relevance

Description

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

Usage

1
2
3
4
## 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 method 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

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
model <- br(toyml, "RANDOM")
pred <- predict(model, toyml)

## Not run: 
# Predict SVM scores
model <- br(toyml, "SVM")
pred <- predict(model, toyml)

# Predict SVM bipartitions running in 4 cores
pred <- predict(model, toyml, probability = FALSE, CORES = 4)

# Passing a specif parameter for SVM predict method
pred <- predict(model, dataset$test, na.action = na.fail)

## End(Not run)

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.