code: def predict(self, X):
      return np.random.randint(0, self.n_classes, shape=(len(X), 1))
  
file_path: modAL/tests/example_tests/multidimensional_data.py
imports: import numpy
  from modAL.batch import uncertainty_batch_sampling
  from modAL.expected_error import expected_error_reduction
  from modAL.models import ActiveLearner
  from modAL.uncertainty import entropy_sampling, margin_sampling
  from sklearn.base import BaseEstimator
label_desc: Use image node_id 3 for calling the MockClassifier obj's underlying member method code with example usage: obj.predict(X) and returns: np