code: def test_mcb_proba():
      (
          pool_classifiers,
          X_dsel,
          y_dsel,
          X_test,
          y_test,
      ) = setup_classifiers()
      rng = np.random.RandomState(123456)
  
      mcb = MCB(pool_classifiers, random_state=rng, DFP=True)
      mcb.fit(X_dsel, y_dsel)
      probas = mcb.predict_proba(X_test)
      expected = np.load(
          "deslib/tests/expected_values/mcb_proba_DFP.npy"
      )
      assert np.allclose(probas, expected)
  
imports: import numpy
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import StandardScaler
  from deslib.dcs.a_posteriori import APosteriori
  from deslib.dcs.a_priori import APriori
  from deslib.dcs.lca import LCA
  from deslib.dcs.mcb import MCB
  from deslib.dcs.mla import MLA
  from deslib.dcs.ola import OLA
  from deslib.dcs.rank import Rank
  from deslib.des import DESKL
  from deslib.des.des_knn import DESKNN
  from deslib.des.des_p import DESP
  from deslib.des.knop import KNOP
  from deslib.des.knora_e import KNORAE
  from deslib.des.knora_u import KNORAU
  from deslib.des.meta_des import METADES
label_desc: Use image node_id 19 for calling a global function with example usage: test_mcb_proba() without return types