Details

Custom nets can be used in this learner either using the survivalmodels::build_pytorch_net utility function or using torch via reticulate. The number of output channels depends on the number of discretised time-points, i.e. the parameters cuts or cutpoints.

Dictionary

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

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

Traits

  • Packages: survivalmodels, distr6, reticulate

  • Predict Types: crank, distr

  • Feature Types: integer, numeric

  • Properties:

References

Kvamme, H., & Borgan, Ø. (2019). Continuous and discrete-time survival prediction with neural networks. ArXiv Preprint ArXiv:1910.06724.

See also

Author

RaphaelS1

Super classes

mlr3::Learner -> mlr3proba::LearnerSurv -> LearnerSurvPCHazard

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

LearnerSurvPCHazard$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

LearnerSurvPCHazard$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# stop example failing with warning if package not installed learner = suppressWarnings(mlr3::lrn("surv.pchazard")) print(learner)
#> <LearnerSurvPCHazard:surv.pchazard> #> * Model: - #> * Parameters: list() #> * Packages: survivalmodels, distr6, reticulate #> * Predict Type: crank #> * Feature types: integer, numeric #> * Properties: -
# available parameters: learner$param_set$ids()
#> [1] "frac" "cuts" "cutpoints" "scheme" #> [5] "cut_min" "num_nodes" "batch_norm" "reduction" #> [9] "dropout" "activation" "custom_net" "device" #> [13] "shrink" "optimizer" "rho" "eps" #> [17] "lr" "weight_decay" "learning_rate" "lr_decay" #> [21] "betas" "amsgrad" "lambd" "alpha" #> [25] "t0" "momentum" "centered" "etas" #> [29] "step_sizes" "dampening" "nesterov" "batch_size" #> [33] "epochs" "verbose" "num_workers" "shuffle" #> [37] "best_weights" "early_stopping" "min_delta" "patience" #> [41] "interpolate" "sub"