code: def setup_classifiers():
      rng = np.random.RandomState(123456)
  
      X_dsel, X_test, X_train, y_dsel, y_test, y_train = load_dataset(
          rng
      )
      # Train a pool of 100 classifiers
      pool_classifiers = AdaBoostClassifier(random_state=rng)
      pool_classifiers.fit(X_train, y_train)
      return pool_classifiers, X_dsel, y_dsel, X_test, y_test
  
file_path: DESlib/deslib/tests/test_des_integration_multiclass.py
imports: import numpy
  from sklearn.datasets import make_classification
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import StandardScaler
  from deslib.dcs.a_priori import APriori
  from deslib.dcs.mcb import MCB
  from deslib.des.des_mi import DESMI
  from deslib.des.des_p import DESP
  from deslib.des.knop import KNOP
  from deslib.des.meta_des import METADES
label_desc: Use image node_id 1 for calling a global function with example usage: setup_classifiers() and returns: pool_classifiers,  X_dsel,  y_dsel,  X_test,  y_test