code: def predict(self, X):
          
          K = self._get_kernel(X, self.X_fit_)
          pred = -numpy.dot(self.coef_, K.T)
          return pred.ravel()
docs: Predict risk score of experiencing an event.
  
          Higher scores indicate shorter survival (high risk),
          lower scores longer survival (low risk).
  
          Parameters
          ----------
          X : array-like, shape = (n_samples, n_features)
              The input samples.
  
          Returns
          -------
          y : ndarray, shape = (n_samples,)
              Predicted risk.