sksurv.meta.Stacking

class sksurv.meta.Stacking(meta_estimator, base_estimators, probabilities=True)

Meta estimator that combines multiple base learners.

By default, base estimators’ output corresponds to the array returned by predict_proba. If predict_proba is not available or probabilities = False, the output of predict is used.

Parameters:
  • meta_estimator (instance of estimator) – The estimator that is used to combine the output of different base estimators.
  • base_estimators (list) – List of (name, estimator) tuples (implementing fit/predict) that are part of the ensemble.
  • probabilities (bool, optional, default: True) – Whether to allow using predict_proba method of base learners, if available.
__init__(meta_estimator, base_estimators, probabilities=True)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(meta_estimator, base_estimators[, …]) Initialize self.
fit(X[, y]) Fit base estimators.
get_params([deep])

Attributes

predict mock imports
predict_log_proba mock imports
predict_proba mock imports
fit(X, y=None, **fit_params)

Fit base estimators.

Parameters:
  • X (array-like, shape = (n_samples, n_features)) – Training data.
  • y (array-like, optional) – Target data if base estimators are supervised.
Returns:

Return type:

self