TaskClassif: Classification Task
In mllg/mlr3: Machine Learning in R - Next Generation

Description Format Construction Fields Methods See Also Examples

This task specializes Task and TaskSupervised for classification problems. The target column is assumed to be a factor. The task_type is set to "classif".

Additional task properties include:

"twoclass": The task is a binary classification problem.
"multiclass": The task is a multiclass classification problem.

Predefined tasks are stored in the mlr3misc::Dictionary mlr_tasks.

R6::R6Class object inheriting from Task/TaskSupervised.

1	t = TaskClassif$new(id, backend, target, positive = NULL)

id :: character(1)
Identifier for the task.
backend :: DataBackend
Either a DataBackend, or any object which is convertible to a DataBackend with as_data_backend(). E.g., a data.frame() will be converted to a DataBackendDataTable.
target :: character(1)
Name of the target column.
positive :: character(1)
Only for binary classification: Name of the positive class. The levels of the target columns are reordered accordingly, so that the first element of $class_names is the positive class, and the second element is the negative class.

All methods from TaskSupervised, and additionally:

class_names :: character()
Returns all class labels of the target column.
positive :: character(1)
Stores the positive class for binary classification tasks, and NA for multiclass tasks. To switch the positive class, assign a level to this field.
negative :: character(1)
Stores the negative class for binary classification tasks, and NA for multiclass tasks.

See TaskSupervised.

Example classification tasks: iris

Other Task: TaskRegr, TaskSupervised, Task, mlr_tasks

data("Sonar", package = "mlbench")
task = TaskClassif$new("sonar", backend = Sonar, target = "Class", positive = "M")

task$task_type
task$formula()
task$truth()
task$class_names
task$positive

# possible properties:
mlr_reflections$task_properties$classif