code: def test_hill_climbing(self):
      models = []
      models += [
          ModelMock(
              "121_RandomForest",
              "Random Forest",
              0.1,
              {
                  "learner": {
                      "max_features": 0.4,
                      "model_type": "Random Forest",
                  },
                  "preprocessing": {},
                  "validation_strategy": {},
              },
          )
      ]
      models += [
          ModelMock(
              "1_RandomForest",
              "Random Forest",
              0.1,
              {
                  "learner": {
                      "max_features": 0.4,
                      "model_type": "Random Forest",
                  },
                  "preprocessing": {},
                  "validation_strategy": {},
              },
          )
      ]
      tuner = MljarTuner(
          {
              "start_random_models": 0,
              "hill_climbing_steps": 1,
              "top_models_to_improve": 2,
          },
          algorithms=["Random Foresrt"],
          ml_task="binary_classification",
          eval_metric="logloss",
          validation_strategy={},
          explain_level=2,
          data_info={"columns_info": [], "target_info": []},
          golden_features=False,
          features_selection=False,
          train_ensemble=False,
          stack_models=False,
          adjust_validation=False,
          boost_on_errors=False,
          kmeans_features=False,
          mix_encoding=False,
          optuna_time_budget=None,
          optuna_init_params={},
          optuna_verbose=True,
          n_jobs=1,
          seed=12,
      )
      ind = 121
      score = 0.1
      for _ in range(5):
          for p in tuner.get_hill_climbing_params(models):
              models += [
                  ModelMock(p["name"], "Random Forest", score, p)
              ]
              score *= 0.1
              self.assertTrue(int(p["name"].split("_")[0]) > ind)
              ind += 1
  
file_path: mljar-supervised/tests/tests_tuner/test_hill_climbing.py
imports: import os
  import unittest
  from supervised.tuner.mljar_tuner import MljarTuner
label_desc: Use image node_id 1 for calling the TunerHillClimbingTest obj's underlying member method code with example usage: obj.test_hill_climbing() without return types