mlr_learners_surv.glmboost: Boosted Generalized Linear Survival Learner

In mlr3learners/mlr3learners.mboost: Learners from mboost package for mlr3

Description

Boosted generalized linear survival learner. Calls mboost::glmboost() from package mboost

Details

distr prediction made by mboost::survFit().

Dictionary

This Learner can be instantiated via the dictionary mlr_learners or with the associated sugar function lrn():

mlr_learners$get("surv.glmboost")
lrn("surv.glmboost")

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvGLMBoost

Methods

Public methods

• LearnerSurvGLMBoost$new()

• LearnerSurvGLMBoost$clone()

Inherited methods

• mlr3::Learner$format()

• mlr3::Learner$help()

• mlr3::Learner$predict()

• mlr3::Learner$predict_newdata()

• mlr3::Learner$print()

• mlr3::Learner$reset()

• mlr3::Learner$train()

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Method new()

Creates a new instance of this R6 class. Importance is supported but fails tests as internally data is coerced to model matrix and original names can't be recovered.

Importance is supported but fails tests as internally data is coerced to model matrix and original names can't be recovered.

description Selected features are extracted with the function mboost::variable.names.mboost(), with used.only = TRUE. return character().

Usage

LearnerSurvGLMBoost$new()

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Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvGLMBoost$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

mlr3learners.mboostbuhlmann_2003

See Also

Dictionary of Learners: mlr3::mlr_learners

Examples

if (requireNamespace("mboost")) {
  learner = mlr3::lrn("surv.glmboost")
  print(learner)

  # available parameters:
  learner$param_set$ids()
}

mlr3learners/mlr3learners.mboost documentation built on Aug. 9, 2020, 10:47 p.m.