class_docstr: Kaplan–Meier estimate of the survival function.
  
  Parameters
  ----------
  conf_level : float, optional, default: 0.95
      The level for a two-sided confidence interval on the survival curves.
  
  conf_type : None or {'log-log'}, optional, default: 'log-log'.
      The type of confidence intervals to estimate.
      If `None`, no confidence intervals are estimated.
      If "log-log", estimate confidence intervals using
      the log hazard or :math:`log(-log(S(t)))`.
  
  See also
  --------
  sksurv.nonparametric.kaplan_meier_estimator
      Functional API of the Kaplan-Meier estimator.
code: def __init__(self, conf_level=0.95, conf_type=None):
      self.conf_level = conf_level
      self.conf_type = conf_type
  
imports: import numbers
  import numpy
  from scipy import stats
  from sklearn.base import BaseEstimator
  from sklearn.utils._param_validation import Interval, StrOptions
  from sklearn.utils.validation import check_array, check_consistent_length, check_is_fitted
  from .util import check_y_survival
label_desc: Use image node_id 1 to create a new SurvivalFunctionEstimator object from inherited base classes: BaseEstimator with example: obj = SurvivalFunctionEstimator(conf_level, conf_type)