mlr_graphs_survaverager: Survival Prediction Averaging Pipeline

In mlr-org/mlr3proba: Probabilistic Supervised Learning for 'mlr3'

Survival Prediction Averaging Pipeline

Description

Wrapper around PipeOpSurvAvg to simplify Graph creation.

Usage

pipeline_survaverager(learners, param_vals = list(), graph_learner = FALSE)

Arguments

learners	(list()) List of LearnerSurvs to average.
param_vals	(list()) Parameters, including weights, to pass to PipeOpSurvAvg.
graph_learner	(logical(1)) If TRUE returns wraps the Graph as a GraphLearner otherwise (default) returns as a Graph.

Value

mlr3pipelines::Graph or mlr3pipelines::GraphLearner

Dictionary

This Graph can be instantiated via the dictionary mlr_graphs or with the associated sugar function ppl():

mlr_graphs$get("survaverager")
ppl("survaverager")

See Also

Other pipelines: mlr_graphs_crankcompositor, mlr_graphs_distrcompositor, mlr_graphs_probregr, mlr_graphs_responsecompositor, mlr_graphs_survbagging, mlr_graphs_survtoclassif_IPCW, mlr_graphs_survtoclassif_disctime, mlr_graphs_survtoregr_pem

Examples

## Not run: 
  library(mlr3)
  library(mlr3pipelines)

  task = tsk("rats")
  pipe = ppl(
    "survaverager",
    learners = lrns(c("surv.kaplan", "surv.coxph")),
    param_vals = list(weights = c(0.1, 0.9)),
    graph_learner = FALSE
  )
  pipe$train(task)
  pipe$predict(task)

## End(Not run)

mlr-org/mlr3proba documentation built on April 12, 2025, 4:38 p.m.