sksurv.metrics.as_cumulative_dynamic_auc_scorer¶

class sksurv.metrics.as_cumulative_dynamic_auc_scorer(estimator, times, tied_tol=1e-08)[source]¶

Wraps an estimator to use cumulative_dynamic_auc() as score function.

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

Parameters

estimator (object) – Instance of an estimator.
times (array-like, shape = (n_times,)) – The time points for which the area under the time-dependent ROC curve is computed. Values must be within the range of follow-up times of the test data survival_test.
tied_tol (float, optional, default: 1e-8) – The tolerance value for considering ties. If the absolute difference between risk scores is smaller or equal than tied_tol, risk scores are considered tied.

estimator_¶

Estimator that was fit.

See also

__init__(estimator, times, tied_tol=1e-08)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`(estimator, times[, tied_tol])	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