tuneThreshold: Tune prediction threshold.

In mlr: Machine Learning in R

Tune prediction threshold.

Description

Optimizes the threshold of predictions based on probabilities. Works for classification and multilabel tasks. Uses BBmisc::optimizeSubInts for normal binary class problems and GenSA::GenSA for multiclass and multilabel problems.

Usage

tuneThreshold(pred, measure, task, model, nsub = 20L, control = list())

Arguments

pred	(Prediction) Prediction object.
measure	(Measure) Performance measure to optimize. Default is the default measure for the task.
task	(Task) Learning task. Rarely neeeded, only when required for the performance measure.
model	(WrappedModel) Fitted model. Rarely neeeded, only when required for the performance measure.
nsub	(integer(1)) Passed to BBmisc::optimizeSubInts for 2class problems. Default is 20.
control	(list) Control object for GenSA::GenSA when used. Default is empty list.

Value

(list). A named list with with the following components: th is the optimal threshold, perf the performance value.

See Also

Other tune: TuneControl, getNestedTuneResultsOptPathDf(), getNestedTuneResultsX(), getResamplingIndices(), getTuneResult(), makeModelMultiplexer(), makeModelMultiplexerParamSet(), makeTuneControlCMAES(), makeTuneControlDesign(), makeTuneControlGenSA(), makeTuneControlGrid(), makeTuneControlIrace(), makeTuneControlMBO(), makeTuneControlRandom(), makeTuneWrapper(), tuneParams()

mlr documentation built on June 22, 2024, 10:51 a.m.