code: def make_learners(generator, indexer, scorer, error_score, **kwargs):
      """Set up generators for the job to be performed"""
      learners = [
          EvalLearner(
              estimator=clone(est).set_params(**params),
              preprocess=p_name,
              indexer=indexer,
              name="%s.%s" % (l_name, i) if i is not None else l_name,
              attr="predict",
              scorer=scorer,
              error_score=error_score,
              **kwargs,
          )
          for p_name, l_name, est, i, params in generator
      ]
      return learners
  
file_path: mlens/mlens/model_selection/_base_functions.py
imports: from __future__ import division
  from collections import Counter
  from ..parallel import EvalLearner, EvalTransformer, Pipeline
  from ..utils.formatting import _assert_format
  from ..utils.checks import assert_valid_estimator
  from ..externals.sklearn.base import clone
label_desc: Use image node_id 8 for calling a global function with example usage: make_learners(generator, indexer, scorer, error_score) and returns: learners