code: def _individual_to_params(individual, name_values):
      return dict(
          (name, values[gene])
          for gene, (name, values) in zip(individual, name_values)
      )
  
imports: from __future__ import division
  import os
  import warnings
  import numpy
  import random
  from deap import base, creator, tools, algorithms
  from collections import defaultdict
  from sklearn.base import clone, is_classifier
  from sklearn.model_selection._validation import _fit_and_score
  from sklearn.model_selection._search import BaseSearchCV, check_cv, _check_param_grid
  from sklearn.metrics import check_scoring
  from sklearn.utils.validation import _num_samples, indexable
label_desc: Use image node_id 6 for calling a global function with example usage: _individual_to_params(individual, name_values) and returns: dict