code: from tune_sklearn import TuneSearchCV
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import RandomForestClassifier
  from skopt.space.space import Real
  
  digits = datasets.load_digits()
  X = digits.data
  y = digits.target
  
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
  
  space = {
      "n_estimators": (100, 200),
      "min_weight_fraction_leaf": Real(0.0, 0.5),
      "min_samples_leaf": (1, 5)
  }
  
  tune_search = TuneSearchCV(
      RandomForestClassifier(),
      space,
      search_optimization="bayesian",
      n_iter=3,
      max_iters=10,
  )
  tune_search.fit(X_train, y_train)
  
  print(tune_search.cv_results_)
  print(tune_search.best_params_)
  
apis: sklearn.model_selection.train_test_split sklearn.datasets.load_digits sklearn.ensemble.RandomForestClassifier