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### Describe the workflow you want to enable
In some cases, it is nice to compare a machine learning classifier with experimental data using ROC or Precision-Recall Curves. For (e.g.) a logarithmic r…
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Currently funding is most extreme when imbalance in open interest is to one side. However, this does *not* account for what fraction the imbalance is of the current open interest cap. This leads to ex…
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This design can help guide how to create all other dependent codes, e.g.,
data = get_dataset("dataset_name")
model = class_imbalance_learner(train = dataset.train, val = dataset.val, approach = 1)…
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As mentioned on [topepo.github.io](https://topepo.github.io/caret/using-your-own-model-in-train.html#illustrative-example-5-optimizing-probability-thresholds-for-class-imbalances), own models can be s…
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xiaoming90
high
# Fewer than expected LP tokens if the pool is imbalanced during vault restoration
## Summary
The vault restoration function intends to perform a proportional deposit. If the pool …
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Thank you for the really great tool!
I was trying to rerun the tutorial, but I got several errors. I would appreciate any help on what could have gone wrong.
Two of them were while running ir.pl.clo…
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- dc removal
- iq imbalance
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Thank you for your great work. I have some questions about your model. Transformer architecture is used twice in your model for different tasks, including corner prediction and edge prediction. I woul…
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The xgboost, RF and NN models all have different ways to handle imbalanced classification datasets by using class-specific weights in their loss functions; but we currently only support this for NN mo…
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The What-If Tool seems really useful.
However for imbalanced data, additional metrics would be great. Being able to use to use Precision-Recall Curves instead of ROC would be amazing. F0.5 Score an…