class_docstr: Container to identify training set.
  
  Samples a random subset from set passed to the `fit` method, to allow
  identification of the training set in a `transform` or `predict` method.
  
  Parameters
  ----------
  size : int
      size to sample. A random subset of size [size, size] will be stored
      in the instance.
code: def __init__(self, size=10):
      if not isinstance(size, Integral):
          raise ValueError("'size' must be an integer. Got %r" % size)
  
      self.size = size
  
file_path: mlens/mlens/utils/id_train.py
imports: from __future__ import division, print_function
  from ..utils.exceptions import NotFittedError
  from ..externals.sklearn.base import BaseEstimator
  from numpy import array_equal, ix_
  from numpy.random import permutation
  from numbers import Integral
label_desc: Use image node_id 1 to create a new IdTrain object from inherited base classes: BaseEstimator with example: obj = IdTrain(size)