code: def test_ola():
      (
          pool_classifiers,
          X_dsel,
          y_dsel,
          X_test,
          y_test,
      ) = setup_classifiers()
  
      ola = OLA(pool_classifiers, DFP=True, with_IH=True, IH_rate=0.1)
      ola.fit(X_dsel, y_dsel)
      assert np.isclose(ola.score(X_test, y_test), 0.9030303030303031)
  
file_path: DESlib/deslib/tests/test_integration_DFP_IH.py
imports: import numpy
  from sklearn.calibration import CalibratedClassifierCV
  from sklearn.datasets import make_classification
  from sklearn.ensemble import BaggingClassifier
  from sklearn.linear_model import Perceptron
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import StandardScaler
  from deslib.dcs.a_posteriori import APosteriori
  from deslib.dcs.mcb import MCB
  from deslib.dcs.ola import OLA
  from deslib.des import DESClustering
  from deslib.des.des_p import DESP
  from deslib.des.knora_u import KNORAU
label_desc: Use image node_id 4 for calling a global function with example usage: test_ola() without return types