hyperparameter_hunter_params.py

params = dict(
        is_unbalance = True,
        learning_rate = Real(0.01, 0.3),
        num_boost_round=Integer(50, 500),
        num_leaves=Integer(31, 255),
        min_child_weight = Real(0.1, 10),
        colsample_bytree= Real(0.5, 1.),
        subsample=Real(0.5, 1.),
        reg_alpha= Real(0.01, 0.1),
        reg_lambda= Real(0.01, 0.1)
    )

extra_params = dict(
    early_stopping_rounds=20,
    feature_name=colnames,
    categorical_feature=categorical_columns
)