mlr_pipeops_trafopred_survregr | R Documentation |
Transform PredictionSurv to PredictionRegr.
Input and output channels are inherited from PipeOpPredTransformer.
The output is the input PredictionSurv transformed to a PredictionRegr. Censoring is ignored.
crank
and lp
predictions are also ignored.
The $state
is a named list
with the $state
elements inherited from PipeOpPredTransformer.
mlr3pipelines::PipeOp
-> mlr3proba::PipeOpTransformer
-> mlr3proba::PipeOpPredTransformer
-> PipeOpPredSurvRegr
new()
Creates a new instance of this R6 class.
PipeOpPredSurvRegr$new(id = "trafopred_survregr")
id
(character(1)
)
Identifier of the resulting object.
clone()
The objects of this class are cloneable with this method.
PipeOpPredSurvRegr$clone(deep = FALSE)
deep
Whether to make a deep clone.
Other PipeOps:
PipeOpPredTransformer
,
PipeOpTaskTransformer
,
PipeOpTransformer
,
mlr_pipeops_survavg
,
mlr_pipeops_trafopred_regrsurv
,
mlr_pipeops_trafotask_regrsurv
,
mlr_pipeops_trafotask_survregr
Other Transformation PipeOps:
mlr_pipeops_trafopred_regrsurv
,
mlr_pipeops_trafotask_regrsurv
,
mlr_pipeops_trafotask_survregr
## Not run: if (requireNamespace("mlr3pipelines", quietly = TRUE)) { library(mlr3) library(mlr3pipelines) library(survival) # simple example pred = PredictionSurv$new(row_ids = 1:10, truth = Surv(1:10, rbinom(10, 1, 0.5)), response = 1:10) po = po("trafopred_survregr") new_pred = po$predict(list(pred = pred))[[1]] print(new_pred) } ## End(Not run)
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