PipeOp has multiple output channels; the members of the input
are forwarded each along a single edge. Therefore, only multiplicities with exactly as many
outnum are accepted.
Multiplicity is currently an experimental features and the implementation or UI
R6Class object inheriting from
PipeOpMultiplicityExply$new(outnum , id = "multiplicityexply", param_vals = list())
Determines the number of output channels.
Identifier of the resulting object, default
param_vals :: named
List of hyperparameter settings, overwriting the hyperparameter settings that would otherwise be set during construction. Default
PipeOpMultiplicityExply has a single input channel named
"input", collecting a
Multiplicity of type any (
"[*]") both during training and prediction.
PipeOpMultiplicityExply has multiple output channels depending on the
"output2" returning the elements of the unclassed input
$state is left empty (
PipeOpMultiplicityExply has no Parameters.
outnum should match the number of elements of the unclassed input
Only fields inherited from
Only methods inherited from
Other Multiplicity PipeOps:
library("mlr3") task1 = tsk("iris") task2 = tsk("mtcars") po = po("multiplicityexply", outnum = 2) po$train(list(Multiplicity(task1, task2))) #> $output1 #> <TaskClassif:iris> (150 x 5) #> * Target: Species #> * Properties: multiclass #> * Features (4): #> - dbl (4): Petal.Length, Petal.Width, Sepal.Length, Sepal.Width #> #> $output2 #> <TaskRegr:mtcars> (32 x 11) #> * Target: mpg #> * Properties: - #> * Features (10): #> - dbl (10): am, carb, cyl, disp, drat, gear, hp, qsec, vs, wt #> po$predict(list(Multiplicity(task1, task2))) #> $output1 #> <TaskClassif:iris> (150 x 5) #> * Target: Species #> * Properties: multiclass #> * Features (4): #> - dbl (4): Petal.Length, Petal.Width, Sepal.Length, Sepal.Width #> #> $output2 #> <TaskRegr:mtcars> (32 x 11) #> * Target: mpg #> * Properties: - #> * Features (10): #> - dbl (10): am, carb, cyl, disp, drat, gear, hp, qsec, vs, wt #>