predict.EPSmodel: Predict Method for Ensemble of Pruned Set Transformation

In utiml: Utilities for Multi-Label Learning

Description

This function predicts values based upon a model trained by eps. Different from the others methods the probability value, is actually, the sum of all probability predictions such as it is described in the original paper.

Usage

## S3 method for class 'EPSmodel'
predict(
  object,
  newdata,
  threshold = 0.5,
  probability = getOption("utiml.use.probs", TRUE),
  ...,
  cores = getOption("utiml.cores", 1),
  seed = getOption("utiml.seed", NA)
)

Arguments

object	Object of class 'EPSmodel'.
newdata	An object containing the new input data. This must be a matrix, data.frame or a mldr object.
threshold	A threshold value for producing bipartitions. (Default: 0.5)
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 prediction. Values higher than 1 require the parallel package. (Default: options("utiml.cores", 1))
seed	An optional integer used to set the seed. (Default: options("utiml.seed", NA))

Value

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

See Also

Ensemble of Pruned Set (EPS)

Examples

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

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