code: def test_kBestSuggestions(self):
      kND = KNearestDatasets(logger=self.logger)
      kND.fit(
          pd.DataFrame([self.krvskp, self.labor]),
          self.runs.loc[:, [233, 234]],
      )
      neighbor = kND.kBestSuggestions(self.anneal, 1)
      np.testing.assert_array_almost_equal(
          [(233, 3.8320802803440586, 1)],
          neighbor,
      )
      neighbors = kND.kBestSuggestions(self.anneal, 2)
      np.testing.assert_array_almost_equal(
          [(233, 3.8320802803440586, 1), (234, 4.367919719655942, 2)],
          neighbors,
      )
      neighbors = kND.kBestSuggestions(self.anneal, -1)
      np.testing.assert_array_almost_equal(
          [(233, 3.8320802803440586, 1), (234, 4.367919719655942, 2)],
          neighbors,
      )
  
      self.assertRaises(
          ValueError, kND.kBestSuggestions, self.anneal, 0
      )
      self.assertRaises(
          ValueError, kND.kBestSuggestions, self.anneal, -2
      )
  
file_path: auto-sklearn/test/test_metalearning/pyMetaLearn/metalearning/test_kND.py
imports: import logging
  import numpy
  import pandas
  from autosklearn.metalearning.metalearning.kNearestDatasets.kND import KNearestDatasets
  from autosklearn.metalearning.metalearning.metrics.misc import get_random_metric
  import unittest
label_desc: Use image node_id 4 for calling the kNDTest obj's underlying member method code with example usage: obj.test_kBestSuggestions() without return types