code: def test_parameter_Kp(Kp, create_pool_classifiers):
      X = np.random.rand(10, 2)
      y = np.ones(10)
      with pytest.raises((ValueError, TypeError)):
          meta = METADES(create_pool_classifiers, Kp=Kp)
          meta.fit(X, y)
  
imports: from unittest.mock import MagicMock
  import numpy
  import pytest
  from sklearn.linear_model import Perceptron
  from sklearn.naive_bayes import GaussianNB
  from sklearn.svm import SVC
  from sklearn.utils.estimator_checks import check_estimator
  from sklearn.utils.validation import check_is_fitted
  from deslib.des.meta_des import METADES
label_desc: Use image node_id 6 for calling a global function with example usage: test_parameter_Kp(Kp, create_pool_classifiers) without return types