How to use the nyoka.skl.skl_to_pmml.get_model_kwargs function in nyoka

col_names : List
        Contains list of feature/column names.
    target_name : String
        Name of the Target column.
    mining_imp_val : tuple
        Contains the mining_attributes,mining_strategy, mining_impute_value.
    categoric_values : tuple
        Contains Categorical attribute names and its values
    model_name : string
        Name of the model

    Returns
    -------
    Returns the MiningModel for the given LGB model
    """
    model_kwargs = sklToPmml.get_model_kwargs(model, col_names, target_name, mining_imp_val,categoric_values)
    mining_models = list()
    mining_models.append(pml.MiningModel(
        modelName=model_name if model_name else "LightGBModel",
        Segmentation=get_outer_segmentation(model, derived_col_names, col_names, target_name, mining_imp_val,categoric_values,model_name),
        **model_kwargs
    ))
    return mining_models

Contains list of feature/column names.
    target_name : String
        Name of the Target column.
    mining_imp_val : tuple
        Contains the mining_attributes,mining_strategy, mining_impute_value.
    categoric_values : tuple
        Contains Categorical attribute names and its values
    model_name : string
        Name of the model

    Returns
    -------
    mining_models :
        Returns Nyoka's MiningModel object
    """
    model_kwargs = sklToPmml.get_model_kwargs(model, col_names, target_name, mining_imp_val, categoric_values)
    if 'XGBRegressor' in str(model.__class__):
        model_kwargs['Targets'] = sklToPmml.get_targets(model, target_name)
    mining_models = list()
    mining_models.append(pml.MiningModel(
        modelName=model_name if model_name else "XGBoostModel",
        Segmentation=get_outer_segmentation(model, derived_col_names, col_names, target_name, mining_imp_val,categoric_values,model_name),
        **model_kwargs
    ))
    return mining_models