code: def _get_regularized_objective(self, df, y, loss, penalty, coef):
      obj = self._get_objective(df, y, loss)
      obj += self.alpha * penalty.regularization(coef)
      return obj
  
imports: import numpy
  from sklearn.utils.extmath import safe_sparse_dot
  from .base import BaseClassifier, BaseRegressor
  from .dataset_fast import get_dataset
  from .loss_fast import Squared
  from .loss_fast import SquaredHinge
  from .loss_fast import MulticlassSquaredHinge
  from .loss_fast import MulticlassLog
  from .penalty import L1Penalty
  from .penalty import L1L2Penalty
  from .penalty import TracePenalty
  from .penalty import SimplexConstraint
  from .penalty import L1BallConstraint
  from .penalty import TotalVariation1DPenalty
label_desc: Use image node_id 3 for calling the _BaseFista obj's underlying member method code with example usage: obj._get_regularized_objective(df, y, loss, penalty, coef) and returns: obj