sksurv.meta.Stacking¶
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class
sksurv.meta.
Stacking
(meta_estimator, base_estimators, probabilities=True)[source]¶ 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.
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__init__
(meta_estimator, base_estimators, probabilities=True)[source]¶ 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])score
(X, y)Returns the concordance index of the prediction.
Attributes
predict
mock imports
predict_log_proba
mock imports
predict_proba
mock imports
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fit
(X, y=None, **fit_params)[source]¶ 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
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score
(X, y)[source]¶ Returns the concordance index of the prediction.
- Parameters
X (array-like, shape = (n_samples, n_features)) – Test samples.
y (structured array, shape = (n_samples,)) – A structured array containing the binary event indicator as first field, and time of event or time of censoring as second field.
- Returns
cindex – Estimated concordance index.
- Return type
float