class_docstr: Base class for cross validation over a grid of parameters.
  
  The best parameter is saved in alpha_cv
  
  This class is currently not used
class_docstr_tok: ["Base","class","for","cross","validation","over","a","grid","of","parameters",".","The","best","parameter","is","saved","in","alpha_cv","This","class","is","currently","not","used"]
code: def __init__(self, alphas):
      self.alphas = alphas
      self.alpha_cv = None
      self.cv_error = None
      self.cv_std = None
  
imports: from abc import ABCMeta, abstractmethod
  from statsmodels.compat.python import with_metaclass
  import itertools
  import numpy
  from statsmodels.gam.smooth_basis import GenericSmoothers, UnivariateGenericSmoother
label_desc: Use image node_id 1 to create a new BasePenaltiesPathCV object from inherited base classes:  with example: obj = BasePenaltiesPathCV(alphas)