def METHOD_NAME(self):
    data_table = self.gen_data(1000, 10, 4)
    select_param = FeatureSelectionParam()
    select_param.variance_coe_param.value_threshold = 0.1
    selection_obj = self._make_selection_obj(data_table)
    filter_obj = get_filter(consts.COEFFICIENT_OF_VARIATION_VALUE_THRES, select_param,
                            model=selection_obj)
    select_properties = SelectionProperties()
    select_properties.set_header(self.header)
    select_properties.set_last_left_col_indexes([x for x in range(len(self.header))])
    select_properties.set_select_all_cols()
    filter_obj.set_selection_properties(select_properties)
    res_select_properties = filter_obj.fit(data_table, suffix='').selection_properties
    result = [self.header[idx] for idx, x in enumerate(self.coe_list)
              if x >= select_param.variance_coe_param.value_threshold]
    self.assertEqual(res_select_properties.all_left_col_names, result)
    self.assertEqual(len(res_select_properties.all_left_col_names), 9)