code: def __init__(
      self,
      alphas=(0.1, 1.0, 10.0),
      fit_intercept=True,
      normalize=False,
      scoring=None,
      cv=None,
      gcv_mode=None,
      store_cv_values=False,
  ):
      self.alphas = alphas
      self.fit_intercept = fit_intercept
      self.normalize = normalize
      self.scoring = scoring
      self.cv = cv
      self.gcv_mode = gcv_mode
      self.store_cv_values = store_cv_values
  
imports: from abc import ABCMeta, abstractmethod
  import warnings
  import numpy
  from scipy import linalg
  from scipy import sparse
  from scipy.sparse import linalg
  from .base import LinearClassifierMixin, LinearModel, _rescale_data
  from .sag import sag_solver
  from ..base import RegressorMixin
  from ..utils.extmath import safe_sparse_dot
  from ..utils.extmath import row_norms
  from ..utils import check_X_y
  from ..utils import check_array
  from ..utils import check_consistent_length
  from ..utils import compute_sample_weight
  from ..utils import column_or_1d
  from ..preprocessing import LabelBinarizer
  from ..model_selection import GridSearchCV
  from ..externals import six
  from ..metrics.scorer import check_scoring
label_desc: Use image node_id 1 to create a new _BaseRidgeCV object from inherited base classes: LinearModel with example: obj = _BaseRidgeCV(alphas, fit_intercept, normalize, scoring, cv, gcv_mode, store_cv_values)