mlr_graphs_survbagging | R Documentation |
Wrapper around PipeOpSubsample and PipeOpSurvAvg to simplify Graph creation.
pipeline_survbagging( learner, iterations = 10, frac = 0.7, avg = TRUE, weights = 1, graph_learner = FALSE )
learner |
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iterations |
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frac |
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avg |
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weights |
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graph_learner |
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Bagging (Bootstrap AGGregatING) is the process of bootstrapping data and aggregating
the final predictions. Bootstrapping splits the data into B
smaller datasets of a given size
and is performed with PipeOpSubsample. Aggregation is
the sample mean of deterministic predictions and a
MixtureDistribution of distribution predictions. This can be
further enhanced by using a weighted average by supplying weights
.
mlr3pipelines::Graph or mlr3pipelines::GraphLearner
mlr3pipelines::GraphLearner
Other pipelines:
mlr_graphs_crankcompositor
,
mlr_graphs_distrcompositor
,
mlr_graphs_probregrcompositor
,
mlr_graphs_survaverager
,
mlr_graphs_survtoregr
## Not run: if (requireNamespace("mlr3pipelines", quietly = TRUE)) { library("mlr3") library("mlr3pipelines") task = tsk("rats") pipe = ppl( "survbagging", learner = lrn("surv.coxph"), iterations = 5, graph_learner = FALSE ) pipe$train(task) pipe$predict(task) } ## End(Not run)
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