code: def test_predict_on_empty_data(self):
      train_set = random_sklearn_dataset(
          10,
          num_classes=3 if self._is_multi_label() else 2,
          multi_label=self._is_multi_label(),
      )
      test_set = SklearnDataset(
          np.array([], dtype=int), np.array([], dtype=int)
      )
  
      clf = self._get_clf()
      clf.fit(train_set)
  
      predictions = clf.predict(test_set)
      self.assertEqual(0, predictions.shape[0])
      self.assertTrue(np.issubdtype(predictions.dtype, np.integer))
  
imports: import unittest
  import numpy
  from scipy.sparse import csr_matrix
  from small_text.base import LABEL_UNLABELED
  from small_text.classifiers.classification import ConfidenceEnhancedLinearSVC, SklearnClassifier
  from small_text.data.datasets import SklearnDataset
  from tests.utils.datasets import random_sklearn_dataset, random_matrix_data
label_desc: Use image node_id 4 for calling the _ClassifierBaseFunctionalityTest obj's underlying member method code with example usage: obj.test_predict_on_empty_data() without return types