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.
Hello, I am Fang Hu. Nice to meet you. I am reading your article. I am a great fan of it. I like it very much. I use this in my research work.However, there are some issues I am a little confused. For example,my AUC is 0.61144214717625,I want to try a different classifier. I found that the class attribute is all 0 in the output file. How do I perform subsequent classification? My idea is that the attribute should be 0 or 1, and then put the balanced file into the classifier for classificationI don't know if my understanding is correct, I am looking forward for your answers. Thank you. Best wishes.