Base class for handling many "preprocessing" operations
that perform essentially the same operation during training and prediction.
Instead implementing a $train_task() and a $predict_task() operation, only
a $get_state() and a $transform() operation needs to be defined,
both of which take one argument: a Task.
Alternatively, analogously to the PipeOpTaskPreproc approach of offering $train_dt()/$predict_dt(),
the $get_state_dt() and $transform_dt() functions may be implemented.
$get_state must not change its input value in-place and must return
something that will be written into $state
(which must not be NULL), transform() should modify its argument in-place;
it is called both during training and prediction.
This inherits from PipeOpTaskPreproc and behaves essentially the same.
Abstract R6Class inheriting from PipeOpTaskPreproc/PipeOp.
PipeOpTaskPreprocSimple$new(id, param_set = ParamSet$new(), param_vals = list(), can_subset_cols = TRUE, packages = character(0), task_type = "Task")
(Construction is identical to PipeOpTaskPreproc.)
id :: character(1)
Identifier of resulting object. See $id slot of PipeOp.
param_set :: ParamSet
Parameter space description. This should be created by the subclass and given to super$initialize().
param_vals :: named list
List of hyperparameter settings, overwriting the hyperparameter settings given in param_set. The
subclass should have its own param_vals parameter and pass it on to super$initialize(). Default list().
can_subset_cols :: logical(1)
Whether the affect_columns parameter should be added which lets the user limit the columns that are
modified by the PipeOpTaskPreprocSimple. This should generally be FALSE if the operation adds or removes
rows from the Task, and TRUE otherwise. Default is TRUE.
packages :: character
Set of all required packages for the PipeOp's $train and $predict methods. See $packages slot.
Default is character(0).
task_type :: character(1)
The class of Task that should be accepted as input and will be returned as output. This
should generally be a character(1) identifying a type of Task, e.g. "Task", "TaskClassif" or
"TaskRegr" (or another subclass introduced by other packages). Default is "Task".
Input and output channels are inherited from PipeOpTaskPreproc.
The output during training and prediction is the Task, modified by $transform() or $transform_dt().
The $state is a named list with the $state elements inherited from PipeOpTaskPreproc.
The parameters are the parameters inherited from PipeOpTaskPreproc.
PipeOpTaskPreprocSimple is an abstract class inheriting from PipeOpTaskPreproc and implementing the
$train_task() and $predict_task() functions. A subclass of PipeOpTaskPreprocSimple may implement the
functions $get_state() and $transform(), or alternatively the functions $get_state_dt() and $transform_dt()
(as well as $select_cols(), in the latter case). This works by having the default implementations of
$get_state() and $transform() call $get_state_dt() and $transform_dt().
Fields inherited from PipeOp.
Methods inherited from PipeOpTaskPreproc, as well as:
get_state(task)
(Task) -> named list
Store create something that will be stored in $state during training phase of PipeOpTaskPreprocSimple.
The state can then influence the $transform() function. Note that $get_state() must return the state, and
should not store it in $state. It is not strictly necessary to implement either $get_state() or $get_state_dt();
if they are not implemented, the state will be stored as list().
This method can optionally be overloaded when inheriting from PipeOpTaskPreprocSimple, together with $transform();
alternatively, $get_state_dt() (optional) and $transform_dt() (and possibly $select_cols(), from PipeOpTaskPreproc)
can be overloaded.
transform(task)
(Task) -> Task
Predict on new data in task, possibly using the stored $state. task should not be cloned, instead it should be
changed in-place. This method is called both during training and prediction phase, and should essentially behave the
same independently of phase. (If this is incongruent with the functionality to be implemented, then it should inherit from
PipeOpTaskPreproc, not from PipeOpTaskPreprocSimple.)
This method can be overloaded when inheriting from PipeOpTaskPreprocSimple, optionally with $get_state();
alternatively, $get_state_dt() (optional) and $transform_dt() (and possibly $select_cols(), from PipeOpTaskPreproc)
can be overloaded.
get_state_dt(dt)
(data.table) -> named list
Create something that will be stored in $state during training phase of PipeOpTaskPreprocSimple.
The state can then influence the $transform_dt() function. Note that $get_state_dt() must return the state, and
should not store it in $state. If neither $get_state() nor $get_state_dt() are overloaded, the state will
be stored as list().
This method can optionally be overloaded when inheriting from PipeOpTaskPreprocSimple, together with $transform_dt()
(and optionally $select_cols(), from PipeOpTaskPreproc); Alternatively, $get_state() (optional) and $transform()
can be overloaded.
transform_dt(dt)
(data.table) -> data.table | data.frame | matrix
Predict on new data in dt, possibly using the stored $state. A transformed object must be returned
that can be converted to a data.table using as.data.table. dt does not need to be copied deliberately, it
is possible and encouraged to change it in-place. This method is called both during training and prediction phase,
and should essentially behave the same independently of phase.
(If this is incongruent with the functionality to be implemented, then it should inherit from
PipeOpTaskPreproc, not from PipeOpTaskPreprocSimple.)
This method can optionally be overloaded when inheriting from PipeOpTaskPreprocSimple, together with $transform_dt()
(and optionally $select_cols(), from PipeOpTaskPreproc); Alternatively, $get_state() (optional) and $transform()
can be overloaded.
Other mlr3pipelines backend related:
Graph,
PipeOpTaskPreproc,
PipeOp,
mlr_pipeops