iaml.actionables.predictors.survival.act_random_survival_forest

[STEP] Random Survival Forest

Classes

ActRandomSurvivalForest

[STEP] Random Survival Forest

Module Contents

class iaml.actionables.predictors.survival.act_random_survival_forest.ActRandomSurvivalForest

Bases: iaml.actionables.predictors.survival._survival_forest.SurvivalForestMemoryMixin, iaml.predictor.Predictor

[STEP] Random Survival Forest

name: str = 'RandomSurvivalForest'

Step’s name.

refs: list[dict[str, Any]]

List of references for this step.

configuration: dict

Configuration of this step (equivalent to hyperparameters for models).

model: sksurv.ensemble.RandomSurvivalForest = None
fit(dataset: iaml.dataset.Dataset)

Fits the step on the given dataset.

Parameters:

dataset (Dataset) – Features and labels.

Returns:

Fitted step.

suitable(dataset: iaml.dataset.Dataset) → bool

Evaluates whether the step is suitable to run with the given dataset.

Parameters:

dataset (Dataset) – Dataset to evaluate on.

Returns:

Whether the step is suitable to run.

priorize(candidate: iaml.candidate.Candidate = None) → float

Evaluates the priority of the step within a pipeline. 0 means the execution of the step should not be prioritized, and 1 means it should be executed early in the pipeline.

Parameters:

candidate (Candidate, optional) – Candidate on which the priority should be evaluated.

Returns:

Value between 0 and 1.