Department of Computer Science Engineering, United International University, Bangladesh;
Department of Computer Science Engineering, United International University, Bangladesh;
Department of Computer Science Engineering, United International University, Bangladesh;
Department of Computer Science Engineering, United International University, Bangladesh;
Department of Computer Science Engineering, United International University, Bangladesh;
Department of Computer Science Engineering, United International University, Bangladesh;
Bagging; Training; Boosting; Training data; Classification algorithms; Conferences; Information technology;
机译:HSDLM:具有深入学习方法的混合采样,用于实施数据分类
机译:使用装袋,增强技术以及是否使用噪声过滤方法来解决班级不平衡问题
机译:基于演化欠采样的装袋集成方法用于不平衡数据分类
机译:用于采用抽样技术袋装的类别不平衡学习的混合方法
机译:通过选择性采样在集合中进行多类不平衡学习。
机译:一种用于不平衡数据学习的新型集成方法:外推-SMOTE SVM套袋
机译:结合混合方法重新定义 - 多级失衡(HAR-MI)和混合采样处理多级不平衡和重叠