mlr3 (version 0.1.2)

LearnerClassif: Classification Learner

Description

This Learner specializes Learner for classification problems.

Many predefined learners can be found in the Dictionary mlr_learners after loading the mlr3learners package.

Arguments

Format

R6::R6Class object inheriting from Learner.

Construction

l = LearnerClassif$new(id, param_set = ParamSet$new(), param_vals = list(), predict_types = character(),
     feature_types = character(), properties = character(), data_formats = "data.table", packages = character())

For a description of the arguments, see Learner. task_type is set to "classif". Possible values for predict_types are a subset of c("response", "prob").

Fields

See Learner.

Methods

See Learner.

See Also

Example classification learners: classif.rpart

Other Learner: LearnerRegr, Learner, mlr_learners

Examples

Run this code
# NOT RUN {
# 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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