This Learner specializes Learner for classification problems.
Many predefined learners can be found in the mlr3misc::Dictionary mlr_learners after loading the mlr3learners package.
R6::R6Class object inheriting from Learner.
For a description of the arguments, see Learner.
task_type is set to
Possible values for
predict_types are passed to and converted by PredictionClassif:
"response": Predicts a class label for each observation in the test set.
"prob": Predicts the posterior probability for each class for each observation in the test set.
Additional learner properties include:
"twoclass": The learner works on binary classification problems.
"multiclass": The learner works on multiclass classification problems.
Example classification learners:
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# get all classification learners from mlr_learners: lrns = mlr_learners$mget(mlr_learners$keys("^classif")) names(lrns) # get a specific learner from mlr_learners: lrn = lrn("classif.rpart") print(lrn) # train the learner: task = tsk("iris") lrn$train(task, 1:120) # predict on new observations: lrn$predict(task, 121:150)$confusion
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