hyperopt_gbm_domain.py

# Define the search space
space = {
    'class_weight': hp.choice('class_weight', [None, 'balanced']),
    'boosting_type': hp.choice('boosting_type', 
                               [{'boosting_type': 'gbdt', 
                                    'subsample': hp.uniform('gdbt_subsample', 0.5, 1)}, 
                                 {'boosting_type': 'dart', 
                                     'subsample': hp.uniform('dart_subsample', 0.5, 1)},
                                 {'boosting_type': 'goss'}]),
    'num_leaves': hp.quniform('num_leaves', 30, 150, 1),
    'learning_rate': hp.loguniform('learning_rate', np.log(0.01), np.log(0.2)),
    'subsample_for_bin': hp.quniform('subsample_for_bin', 20000, 300000, 20000),
    'min_child_samples': hp.quniform('min_child_samples', 20, 500, 5),
    'reg_alpha': hp.uniform('reg_alpha', 0.0, 1.0),
    'reg_lambda': hp.uniform('reg_lambda', 0.0, 1.0),
    'colsample_bytree': hp.uniform('colsample_by_tree', 0.6, 1.0)
}