Cost-sensitive learning is a popular paradigm to address class-imbalance learning (CIL) problem. Traditional cost-sensitive learning approaches always solve CIL problem by assigning a constant higher training error penalty for all minority instances than that of majority instances. but ignore the significance of location information. Therefore. https://ozautosportes.shop/product-category/3hv/