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This method is a solution to imbalanced data problem.
This is a hybrid implementation of oversampling method Synthetic Minority Oversampling Technique (SMOTE) and undersampling method called Sample Subset Optimization and Particle Swarm Optimization (SSO-PSO) to solve Imbalanced data problem.
This is a hybrid intelligent sampling technique to tackle class-imbalance in real world datasets. To know more about it please refer the link: https://www.sciencedirect.com/science/article/pii/S1568494619300924. Cite our paper, if you are using it in your research work. The citation of our paper is: Susan, Seba, and Amitesh Kumar. "SSOMaj-SMOTE-SSOMin: Three-step intelligent pruning of majority and minority samples for learning from imbalanced datasets." Applied Soft Computing 78 (2019): 141-149.
This is a hybrid intelligent sampling technique to tackle class-imbalance in real world datasets. To know more about it please refer the link: https://www.sciencedirect.com/science/article/pii/S1568494619300924. Cite our paper, if you are using it in your research work. The citation of our paper is: Susan, Seba, and Amitesh Kumar. "SSOMaj-SMOTE-SSOMin: Three-step intelligent pruning of majority and minority samples for learning from imbalanced datasets." Applied Soft Computing 78 (2019): 141-149.
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