def get_param_grid(pipeline_name=None):
    """Returns dictionary with hyperparameter values to search

    Parameters
    ----------
    pipeline_name : str, optional
        Pipeline name. Should be formatted as
        <name>_comp_<config>_<num_groups>-groups. For example,
        pipeline_name=BDT_comp_IC86.2012_2-groups (default is None).

    Returns
    -------
    param_grid : dict
        Dictionary with hyperparameter names / values to be passed to
        GridSearchCV.
    """
    if pipeline_name is None:
        raise ValueError('Must enter a value for pipeline_name.')
    if 'BDT' in pipeline_name:
        param_grid = {'classifier__n_estimators': [10, 50, 100, 150, 200, 250, 300],
                      'classifier__max_depth': list(range(1, 11)),
                      'classifier__learning_rate': [0.1, 0.5, 0.8]}
    elif 'xgboost' in pipeline_name:
        # param_grid = {'classifier__n_estimators': [100, 150, 200],
        #               'classifier__max_depth': list(range(3, 7)),
        #               'classifier__learning_rate': [0.1, 0.15, 0.2]}
        param_grid = {'classifier__n_estimators': [100, 150, 200, 250, 300, 400, 500, 600],
                      'classifier__max_depth': list(range(3, 11)),
                      'classifier__learning_rate': [0.01, 0.025, 0.05, 0.1, 0.15, 0.2],
                      # 'classifier__subsample': [0.5, 0.75, 1.0],
                      }
    else:
        raise ValueError('Invalid pipeline entered: {}'.format(pipeline_name))

    return param_grid