code: def intercept_(self):
          
          if getattr(self, 'booster', None) is not None and self.booster != 'gblinear':
              raise AttributeError('Intercept (bias) is not defined for Booster type {}'
                                   .format(self.booster))
          b = self.get_booster()
          return np.array(json.loads(b.get_dump(dump_format='json')[0])['bias'])
docs: Intercept (bias) property
  
          .. note:: Intercept is defined only for linear learners
  
              Intercept (bias) is only defined when the linear model is chosen as base
              learner (`booster=gblinear`). It is not defined for other base learner types, such
              as tree learners (`booster=gbtree`).
  
          Returns
          -------
          intercept_ : array of shape ``(1,)`` or ``[n_classes]``