docstr: Returns the concordance index of the prediction.
  
  Parameters
  ----------
  X : array-like, shape = (n_samples, n_features)
      Test samples.
  
  y : structured array, shape = (n_samples,)
      A structured array containing the binary event indicator
      as first field, and time of event or time of censoring as
      second field.
  
  Returns
  -------
  cindex : float
      Estimated concordance index.
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code: def score(self, X, y):
      """Returns the concordance index of the prediction.
  
      Parameters
      ----------
      X : array-like, shape = (n_samples, n_features)
          Test samples.
  
      y : structured array, shape = (n_samples,)
          A structured array containing the binary event indicator
          as first field, and time of event or time of censoring as
          second field.
  
      Returns
      -------
      cindex : float
          Estimated concordance index.
      """
      from .metrics import concordance_index_censored
  
      name_event, name_time = y.dtype.names
  
      risk_score = self.predict(X)
      if not getattr(self, "_predict_risk_score", True):
          risk_score *= (
              -1
          )  # convert prediction on time scale to risk scale
  
      result = concordance_index_censored(
          y[name_event], y[name_time], risk_score
      )
      return result[0]
  
imports: import numpy
label_desc: Use image node_id 4 for calling the SurvivalAnalysisMixin obj's underlying member method code with example usage: obj.score(X, y) and returns: result