mlr_tasks {mlr3} | R Documentation |
Dictionary of Tasks
Description
A simple mlr3misc::Dictionary storing objects of class Task.
Each task has an associated help page, see mlr_tasks_[id]
.
This dictionary can get populated with additional tasks by add-on packages, e.g. mlr3data, mlr3proba or mlr3cluster. mlr3oml allows to interact with OpenML.
For a more convenient way to retrieve and construct tasks, see tsk()
/tsks()
.
Format
R6::R6Class object inheriting from mlr3misc::Dictionary.
Methods
See mlr3misc::Dictionary.
S3 methods
-
as.data.table(dict, ..., objects = FALSE)
mlr3misc::Dictionary ->data.table::data.table()
Returns adata.table::data.table()
with columns "key", "label", "task_type", "nrow", "ncol", "properties", and the number of features of type "lgl", "int", "dbl", "chr", "fct" and "ord", respectively. Ifobjects
is set toTRUE
, the constructed objects are returned in the list column namedobject
.
See Also
Sugar functions: tsk()
, tsks()
Extension Packages: mlr3data
Other Dictionary:
mlr_learners
,
mlr_measures
,
mlr_resamplings
,
mlr_task_generators
Other Task:
Task
,
TaskClassif
,
TaskRegr
,
TaskSupervised
,
TaskUnsupervised
,
mlr_tasks_boston_housing
,
mlr_tasks_breast_cancer
,
mlr_tasks_german_credit
,
mlr_tasks_iris
,
mlr_tasks_mtcars
,
mlr_tasks_penguins
,
mlr_tasks_pima
,
mlr_tasks_sonar
,
mlr_tasks_spam
,
mlr_tasks_wine
,
mlr_tasks_zoo
Examples
as.data.table(mlr_tasks)
task = mlr_tasks$get("penguins") # same as tsk("penguins")
head(task$data())
# Add a new task, based on a subset of penguins:
data = palmerpenguins::penguins
data$species = factor(ifelse(data$species == "Adelie", "1", "0"))
task = TaskClassif$new("penguins.binary", data, target = "species", positive = "1")
# add to dictionary
mlr_tasks$add("penguins.binary", task)
# list available tasks
mlr_tasks$keys()
# retrieve from dictionary
mlr_tasks$get("penguins.binary")
# remove task again
mlr_tasks$remove("penguins.binary")