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 class 'TaskClassif'
as_task_classif(x, clone = FALSE, ...)
# S3 method for class 'data.frame'
as_task_classif(
x,
target = NULL,
id = deparse1(substitute(x)),
positive = NULL,
label = NA_character_,
...
)
# S3 method for class 'matrix'
as_task_classif(
x,
target,
id = deparse1(substitute(x)),
label = NA_character_,
...
)
# S3 method for class 'Matrix'
as_task_classif(
x,
target,
id = deparse1(substitute(x)),
label = NA_character_,
...
)
# S3 method for class 'DataBackend'
as_task_classif(
x,
target = NULL,
id = deparse1(substitute(x)),
positive = NULL,
label = NA_character_,
...
)
# S3 method for class 'TaskRegr'
as_task_classif(
x,
target = NULL,
drop_original_target = FALSE,
drop_levels = TRUE,
...
)
# S3 method for class 'formula'
as_task_classif(
x,
data,
id = deparse1(substitute(data)),
positive = NULL,
label = NA_character_,
...
)
Arguments
- x
(any)
Object to convert.- ...
(any)
Additional arguments.- clone
(
logical(1)
)
IfTRUE
, ensures that the returned object is not the same as the inputx
.- 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)
)
IfFALSE
(default), the original target is added as a feature. Otherwise the original target is dropped.- drop_levels
(
logical(1)
)
IfTRUE
(default), unused levels of the new target variable are dropped.- data
(
data.frame()
)
Data frame containing all columns referenced in formulax
.
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