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__(self, meta_estimator, base_estimators, probabilities=True)

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

Methods

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

Attributes

predict() mock imports
predict_log_proba() mock imports
predict_proba() mock imports
fit(self, 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:
self