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Hi everyone,
As the TCP implementation goes on, I realized that the current settings for the training (i.e., 60 epochs with LR decay after 30 epochs) result in severe overfitting to **LANE FOLLOWI…
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I was wondering how possible it would be to incorporate the sampling preprocessors in Imbalanced learn?
[https://github.com/scikit-learn-contrib/imbalanced-learn
](https://github.com/scikit-learn-…
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# Mutz et al 2019
## Main focus:
Find whether there are statistical evidence to support the argument: “Covariates may be included because their distribution is unbalanced across treatment groups.”…
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Imbalanced package
imbalanced-learn documentation
https://github.com/scikit-learn-contrib/imbalanced-learn
https://imbalanced-learn.org/stable/
2022/04
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Hi, big fan of the project and the talk at scipy 2018. I am currently trying to use UMAP for a kaggle competition and was wondering if umap can be affected by data imbalance in anyway and if yes what …
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The NVT equilibration (using cluster_equilibrate) of FMO currently suffers from 400% load imbalance on 72 cores -- 12 for PME. Cause not known.
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Need to deal with the major in-balance in the size of the two classes (bga and non_algae).
Below are some good links that describe the importance of making sure the classes are balanced in size an…
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Hi All,
I defined a "bad wine" if it had a quality score less than 5, 'good wine' if greater than 5 but less than 7, and the rest would be considered as "Excellent"
The red_wine and white_wine d…
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Hi,
Thank you for this implementation. It is my understanding that some contrastive frameworks build upon entropy maximization, which leads to inapplicability in the contexts of imbalanced datasets…