R: Tune prediction threshold.

tuneThreshold {mlr} | R Documentation

## 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`, `makeModelMultiplexerParamSet`, `makeModelMultiplexer`, `makeTuneControlCMAES`, `makeTuneControlDesign`, `makeTuneControlGenSA`, `makeTuneControlGrid`, `makeTuneControlIrace`, `makeTuneControlMBO`, `makeTuneControlRandom`, `makeTuneWrapper`, `tuneParams`

[Package mlr version 2.14.0 Index]