survivalpredict.estimators.KaplanMeierSurvivalEstimator

class survivalpredict.estimators.KaplanMeierSurvivalEstimator

The Kaplan-Meier estimate of the survival estimation.

Kaplan-Meier is a univariate non-parametric survival curve estimation. It can be useful as a baseline/dummy estimator.

Methods

fit(X, times, events[, strata, check_input, ...])

Fit model.

fit_predict(*args, **kwargs)

Fit model and Build survival curves.

predict(X[, strata, max_time])

Build survival curves on an array of vectors X.
__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)

fit(X, times, events[, strata, check_input, ...])

Fit model.

fit_predict(*args, **kwargs)

Fit model and Build survival curves.

get_metadata_routing()

Get metadata routing of this object.

get_params([deep])

Get parameters for this estimator.

predict(X[, strata, max_time])

Build survival curves on an array of vectors X.

set_fit_request(*[, check_input, events, ...])

Configure whether metadata should be requested to be passed to the fit method.

set_params(**params)

Set the parameters of this estimator.

set_predict_request(*[, max_time, strata])

Configure whether metadata should be requested to be passed to the predict method.
fit(X, times, events, strata=None, check_input=True, times_start=None)

Fit model.

Parameters:

  • X (array-like of shape (n_samples, n_features)) – Training data.

  • times (array-like of shape (n_samples), dtype=np.int64) – Point in time last observed.

  • events (array-like of shape (n_samples), dtype=np.bool_) – Experianed event.

  • strata (array-like of shape (n_samples,), dtype=np.int64, default=None) – If passed in, associated strata for per observation.

  • check_input (bool, default=True) – If True, validates and casts inputs.

  • times_start (array-like of shape (n_samples, dtype=np.int64), default=None) – Starting point for observation. If not passed in, all times_start times are assumed to be 0.

Returns:

Fitted Estimator.

Return type:

object

fit_predict(*args, **kwargs)

Fit model and Build survival curves.

predict(X, strata=None, max_time=None)

Build survival curves on an array of vectors X.

Parameters:

  • X (array-like of shape (n_samples, n_features)) – Predicting data.

  • strata (array-like of shape (n_samples,), dtype=np.int64, default=None) – If passed in, associated strata for per observation.

  • max_time (int, default=None) – Maximum time of built survival curves. If none, maximum time is max time seen on training data.

Returns:

The estimated survival curves, the left-most column is the probability of survival at time 1, and the right-most column ends at max_time.

Return type:

ndarray of shape (n_samples, max_time), dtype=np.float64