Christos Aridas
Christos Aridas
Thanks for the clarification @dvro. That could be placed in the wiki!
[MetaCost](https://homes.cs.washington.edu/~pedrod/papers/kdd99.pdf) could be a nice addition.
@mwydmuch PRs are always welcome. With the addition of #360 will start the ensemble methods module and I think that we'll deprecate the current ensemble based samplers.
@glemaitre do you think that we should have requirements, e.g. number of citations, before we merge an implementation into the package?
@glemaitre I was thinking to ask @mwydmuch to include a comparison with the `BalancedBaggingClassifier` (#360) but I thought that would be a nice addition after the implementation, and not a...
Cluster Based Oversampling1 1. Jo, T., & Japkowicz, N. (2004). Class imbalances versus small disjuncts. ACM Sigkdd Explorations Newsletter, 6(1), 40-49.
Random-SMOTE1 1. Dong, Y., & Wang, X. (2011). A new over-sampling approach: random-SMOTE for learning from imbalanced data sets. In International Conference on Knowledge Science, Engineering and Management
Supervised Over-Sampling1 1.Hu, J., He, X., Yu, D. J., Yang, X. B., Yang, J. Y., & Shen, H. B. (2014). A new supervised over-sampling algorithm with application to protein-nucleotide binding...
@glemaitre #460 is closed but #457 is still open and probably relevant. Could we close this PR in favor of new one in the future? It is two years old.
> Hi all, I was wondering if someone is working on this or similar implementation of MLSMOTE. I am interested in trying this algorithm. I might have some time to...