search

nickkunz / smogn

Synthetic Minority Over-Sampling Technique for Regression
https://pypi.org/project/smogn
GNU General Public License v3.0
319 stars 78 forks source link

Over-sampling #43

Open shaimove opened 1 year ago

shaimove commented 1 year ago

Hi, I am working on a regression problem, and I want to use SMOTER' the problem is that I don't understand how to oversample my data significantly. My input dataframe size is [716,3457], and the output is about the same size ([1068,3457]). I read the function and the examples, and couldn't understand how to do it. Specifically, I using DeepSMOTE method to create additional synthetic signals, so the oversampling is done on the latent space after the encoder. Thanks, Sharon

nickkunz commented 1 year ago

Hello Sharon,

Thank you for your question. I would encourage you to review the paper found in the Reference section of the repo. Let me know if this helps.

Branco, P., Torgo, L., Ribeiro, R. (2017). SMOGN: A Pre-Processing Approach for Imbalanced Regression. Proceedings of Machine Learning Research, 74:36-50. http://proceedings.mlr.press/v74/branco17a/branco17a.pdf.