code: def _assert_importances_good(perm, feat_names):
      importances = dict(zip(feat_names, perm.feature_importances_))
      print(perm.scores_)
      print(importances)
      assert importances["LSTAT"] > importances["NOX"]
      return importances
  
imports: import pytest
  import numpy
  from sklearn.base import is_classifier, is_regressor
  from sklearn.svm import SVR, SVC
  from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
  from sklearn.model_selection import train_test_split, cross_val_score
  from sklearn.pipeline import make_pipeline
  from sklearn.feature_selection import SelectFromModel
  from sklearn.linear_model import LogisticRegression
  import eli5
  from eli5.sklearn import PermutationImportance
  from .utils import format_as_all
label_desc: Use image node_id 2 for calling a global function with example usage: _assert_importances_good(perm, feat_names) and returns: importances