class_docstr: BaseCV class. It computes the cross validation error of a given model.
  All the cross validation classes can be derived by this one
  (e.g. GamCV, LassoCV,...)
class_docstr_tok: ["BaseCV","class",".","It","computes","the","cross","validation","error","of","a","given","model",".","All","the","cross","validation","classes","can","be","derived","by","this","one","(","e.g",".","GamCV",",","LassoCV",",","...",")"]
code: def _error(self, train_index, test_index, **kwargs):
      # train the model on the train set
      #   and returns the error on the test set
      pass
  
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 3 for calling the BaseCV obj's underlying member method code with example usage: obj._error(train_index, test_index) without return types