Convert to a Classification Task — as_task

Convert object to a TaskClassif. This is a S3 generic. mlr3 ships with methods for the following objects:

TaskClassif: ensure the identity
formula, data.frame(), matrix(), Matrix::Matrix() and DataBackend: provides an alternative to the constructor of TaskClassif.
TaskRegr: Calls convert_task().

Note that the target column will be converted to a factor(), if possible.

Usage

as_task_classif(x, ...)

# S3 method for TaskClassif
as_task_classif(x, clone = FALSE, ...)

# S3 method for data.frame
as_task_classif(
  x,
  target = NULL,
  id = deparse(substitute(x)),
  positive = NULL,
  label = NA_character_,
  ...
)

# S3 method for matrix
as_task_classif(
  x,
  target,
  id = deparse(substitute(x)),
  label = NA_character_,
  ...
)

# S3 method for Matrix
as_task_classif(
  x,
  target,
  id = deparse(substitute(x)),
  label = NA_character_,
  ...
)

# S3 method for DataBackend
as_task_classif(
  x,
  target = NULL,
  id = deparse(substitute(x)),
  positive = NULL,
  label = NA_character_,
  ...
)

# S3 method for TaskRegr
as_task_classif(
  x,
  target = NULL,
  drop_original_target = FALSE,
  drop_levels = TRUE,
  ...
)

# S3 method for formula
as_task_classif(
  x,
  data,
  id = deparse(substitute(data)),
  positive = NULL,
  label = NA_character_,
  ...
)

Arguments

x: (any)
Object to convert.
...: (any)
Additional arguments.
clone: (logical(1))
If TRUE, ensures that the returned object is not the same as the input x.
target: (character(1))
Name of the target column.
id: (character(1))
Id for the new task. Defaults to the (deparsed and substituted) name of the data argument.
positive: (character(1))
Level of the positive class. See TaskClassif.
label: (character(1))
Label for the new instance.
drop_original_target: (logical(1))
If FALSE (default), the original target is added as a feature. Otherwise the original target is dropped.
drop_levels: (logical(1))
If TRUE (default), unused levels of the new target variable are dropped.
data: (data.frame())
Data frame containing all columns referenced in formula x.

Value

TaskClassif.

Examples

as_task_classif(palmerpenguins::penguins, target = "species")
#> <TaskClassif:palmerpenguins::penguins> (344 x 8)
#> * Target: species
#> * Properties: multiclass
#> * Features (7):
#>   - int (3): body_mass_g, flipper_length_mm, year
#>   - dbl (2): bill_depth_mm, bill_length_mm
#>   - fct (2): island, sex