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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://www.hindirochakkahaniya.com/

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