Extends the generic stats::predict() with a method for Learner. Note that this function is intended as glue code to be used in third party packages. We recommend to work with the Learner directly, i.e. calling learner$predict() or learner$predict_newdata() directly.

Performs the following steps:

  • Sets additional hyperparameters passed to this function.

  • Creates a Prediction object by calling learner$predict_newdata().

  • Returns (subset of) Prediction.

# S3 method for Learner
predict(object, newdata, predict_type = NULL, ...)

Arguments

object

(Learner)
Any Learner.

newdata

(data.frame())
New data to predict on.

predict_type

(character(1))
The predict type to return. Set to <Prediction> to retrieve the complete Prediction object. If set to NULL (default), the first predict type for the respective class of the Learner as stored in mlr_reflections is used.

...

(any)
Hyperparameters to pass down to the Learner.

Examples

task = tsk("spam") learner = lrn("classif.rpart", predict_type = "prob") learner$train(task) predict(learner, task$data(1:3), predict_type = "response")
#> [1] spam spam spam #> Levels: spam nonspam
predict(learner, task$data(1:3), predict_type = "prob")
#> spam nonspam #> [1,] 0.8513514 0.14864865 #> [2,] 0.9339623 0.06603774 #> [3,] 0.9339623 0.06603774
predict(learner, task$data(1:3), predict_type = "<Prediction>")
#> <PredictionClassif> for 3 observations: #> row_id truth response prob.spam prob.nonspam #> 1 spam spam 0.8513514 0.14864865 #> 2 spam spam 0.9339623 0.06603774 #> 3 spam spam 0.9339623 0.06603774