code: def _toSKLGLM(self, model, is_classifier):
          
          py_cls = type(model)
          skl_cls = self._spark2skl_classes[py_cls]
          intercept = model.intercept
          weights = model.coefficients
          skl = skl_cls()
          skl.intercept_ = np.float64(intercept)
          skl.coef_ = weights.toArray().reshape(1, -1)
          if is_classifier:
              skl.classes_ = np.array([0, 1])
          return skl
docs: Private method for converting a GLM to a scikit-learn model
          TODO: Add model parameters as well.