Getting the results from study object

study_results.py

# Getting the best trial:
print(f"The best trial is : \n{study.best_trial}")
# >> Output:
#The best trial is : 
#FrozenTrial(number=18, value=0.9631114824097281, datetime_start=datetime.datetime(2020, 8, 16, 14, 24, 37, 407344), datetime_complete=datetime.datetime(2020, 8, 16, 14, 24, 37, 675114), params={'classifier': 'RandomForest', 'rf_n_estimators': 153, 'rf_max_depth': 21},
#distributions={'classifier': CategoricalDistribution(choices=('LogReg', 'RandomForest')), 'rf_n_estimators': IntUniformDistribution(high=1000, low=10, step=1), 'rf_max_depth': IntLogUniformDistribution(high=32, low=2, step=1)}, user_attrs={}, system_attrs={}, intermediate_values={}, trial_id=18, state=TrialState.COMPLETE)

# Getting the best score:
print(f"The best value is : \n{study.best_value}")
# >> Output:
# 0.9631114824097281

# Getting the best parameters:
print(f"The best parameters are : \n{study.best_params}")
# >> Output:
# {'classifier': 'RandomForest', 'rf_n_estimators': 153, 'rf_max_depth': 21}