sksurv.metrics.as_integrated_brier_score_scorer¶

class sksurv.metrics.as_integrated_brier_score_scorer(estimator, times)[source]¶

Wraps an estimator to use the negative of integrated_brier_score() as score function.

The estimator needs to be able to estimate survival functions via a predict_survival_function method.

See the User Guide for using it for hyper-parameter optimization.

Parameters

estimator (object) – Instance of an estimator that provides predict_survival_function.
times (array-like, shape = (n_times,)) – The time points for which to estimate the Brier score. Values must be within the range of follow-up times of the test data survival_test.

estimator_¶

Estimator that was fit.

See also

__init__(estimator, times)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(estimator, times)	Initialize self.
`fit`(X, y, **fit_params)
`score`(X, y)	Returns the score on the given data.

Attributes

`predict`	mock imports
`predict_cumulative_hazard_function`	mock imports
`predict_survival_function`	mock imports

score(X, y)[source]¶

Returns the score on the given data.

Parameters

X (array-like of shape (n_samples, n_features)) – Input data, where n_samples is the number of samples and n_features is the number of features.
y (array-like of shape (n_samples,)) – Target relative to X for classification or regression; None for unsupervised learning.

Returns

score

Return type

float