survivalpredict.pipeline.make_sklearn_survival_pipeline

survivalpredict.pipeline.make_sklearn_survival_pipeline(*steps_no_names, max_time, memory=None)

Construct a SklearnSurvivalPipeline from given steps.

This is a shorthand for the SklearnSurvivalPipeline constructor; it does not require, and does not permit, naming the steps. Instead, their names will be set to the lowercase of their types automatically.

Parameters:

• *steps_no_names (list of Estimator objects) – List of class instances that are chained together. The class instances are assumped to be scikit-learn transformers/survivalpredict StrataBuilders/StrataColumnTransformers. The final instance is assumed to be a survivalpredict estimator predictor.

• max_time (int) – Maximum time for building survival curves.

• memory (str or object with the joblib.Memory interface, default=None Used) – Used to cache the fitted transformers of the pipeline. The last step will never be cached, even if it is a transformer. By default, no caching is performed. If a string is given, it is the path to the caching directory. Enabling caching triggers a clone of the transformers before fitting. Therefore, the transformer instance given to the pipeline cannot be inspected directly. Use the attribute named_steps or steps to inspect estimators within the pipeline. Caching the transformers is advantageous when fitting is time consuming.