R: Query properties of learners.

LearnerProperties {mlr} | R Documentation

## Query properties of learners.

### Description

Properties can be accessed with `getLearnerProperties(learner)`, which returns a character vector.

The learner properties are defined as follows:

numerics, factors, ordered

  Can numeric, factor or ordered factor features be handled?

functionals

  Can an arbitrary number of functional features be handled?

single.functional

  Can exactly one functional feature be handled?

missings

  Can missing values in features be handled?

weights

  Can observations be weighted during fitting?

oneclas, twoclass, multiclass

  Only for classif: Can one-class, two-class or multi-class classification problems be handled?

class.weights

  Only for classif: Can class weights be handled?

rcens, lcens, icens

  Only for surv: Can right, left, or interval censored data be handled?

prob

  For classif, cluster, multilabel, surv: Can probabilites be predicted?

se

  Only for regr: Can standard errors be predicted?

oobpreds

  Only for classif, regr and surv: Can out of bag predictions be extracted from the trained model?

featimp

  For classif, regr, surv: Does the model support extracting information on feature importance?

### Usage

    getLearnerProperties(learner)

    hasLearnerProperties(learner, props)

### Arguments

`learner` | (Learner | `character(1)`) The learner. If you pass a string the learner will be created via makeLearner.
`props` | (character) Vector of properties to query.

### Value

`getLearnerProperties` returns a character vector with learner properties. `hasLearnerProperties` returns a logical vector of the same length as `props`.

### See Also

Other learner: `getClassWeightParam`, `getHyperPars`, `getLearnerId`, `getLearnerPackages`, `getLearnerParVals`, `getLearnerParamSet`, `getLearnerPredictType`, `getLearnerShortName`, `getLearnerType`, `getParamSet`, `helpLearnerParam`, `helpLearner`, `makeLearners`, `makeLearner`, `removeHyperPars`, `setHyperPars`, `setId`, `setLearnerId`, `setPredictThreshold`, `setPredictType`

[Package mlr version 2.13 Index]