tuneThreshold: Tune prediction threshold.

In Najah-lshanableh/R-data-mining2: Machine Learning in R

Description

Optimizes the threshold of predictions based on probabilities. Works for classification and multilabel tasks. Uses optimizeSubInts for normal binary class problems and cma_es 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 optimizeSubInts for 2class problems. Default is 20.
control	[list] Control object for cma_es 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, getTuneResult, makeModelMultiplexerParamSet, makeModelMultiplexer, makeTuneControlCMAES, makeTuneControlDesign, makeTuneControlGenSA, makeTuneControlGrid, makeTuneControlIrace, makeTuneControlMBO, makeTuneControlRandom, makeTuneWrapper, tuneParams

Najah-lshanableh/R-data-mining2 documentation built on May 6, 2019, 10:11 a.m.