code: def test_sm2_ind_cat():
      # Binary
      col = 5
      ind = new_imp_sm2.na_where[col]
      orig = iris_new.values[ind, col]
      imps = new_imp_sm2[0, col, iterations]
      acc = (imps == orig).mean()
      assert acc > 0.6
  
      # Multiclass
      col = 4
      ind = new_imp_sm2.na_where[col]
      orig = iris_new.values[ind, col]
      imps = new_imp_sm2[0, col, iterations]
      acc = (imps == orig).mean()
      assert acc > 0.7
  
imports: from sklearn.datasets import load_iris
  import pandas
  import numpy
  import miceforest
  from miceforest.utils import logistic_function
  from sklearn.metrics import roc_auc_score
  from miceforest import mean_match_fast_cat, mean_match_default, mean_match_shap
label_desc: Use image node_id 8 for calling a global function with example usage: test_sm2_ind_cat() without return types