synthcity.plugins.core.models.time_to_event.tte_survival_function_regression module

class SurvivalFunctionTimeToEvent(time_points: int = 100, model_search_n_iter: Optional[int] = None, device: Any = device(type='cpu'), **kwargs: Any)

Bases: synthcity.plugins.core.models.time_to_event._base.TimeToEventPlugin

fit(X: pandas.core.frame.DataFrame, T: pandas.core.series.Series, Y: pandas.core.series.Series) → synthcity.plugins.core.models.time_to_event._base.TimeToEventPlugin

Training logic

static hyperparameter_space(**kwargs: Any) → List[synthcity.plugins.core.distribution.Distribution]

Returns the hyperparameter space for the derived plugin.

static load(buff: bytes) → Any

static load_dict(representation: dict) → Any

static name() → str

The name of the plugin.

predict(X: pandas.core.frame.DataFrame) → pandas.core.series.Series

Predict time-to-event

predict_any(X: pandas.core.frame.DataFrame, E: pandas.core.series.Series) → pandas.core.series.Series

Predict time-to-event or censoring

classmethod sample_hyperparameters(*args: Any, **kwargs: Any) → Dict[str, Any]

Sample value from the hyperparameter space for the current plugin.

save() → bytes

save_dict() → dict

save_to_file(path: pathlib.Path) → bytes

static version() → str

API version