predict.NSmodel: Predict Method for Nested Stacking

In utiml: Utilities for Multi-Label Learning

Description

This function predicts values based upon a model trained by ns. The scores of the prediction was adapted once this method uses a correction of labelsets to predict only classes present on training data. To more information about this implementation see subset_correction.

Usage

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

Arguments

object	Object of class 'NSmodel'.
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	Ignored because this method does not support multi-core.
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

Nested Stacking (NS)

Examples

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


# Predict SVM bipartitions
pred <- predict(model, toyml, probability = FALSE)

# 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.