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first, thank you for this great framework, my question is; what is the best way to define variables for imbalanced classification (with a lot of categories) for which in each batch they might be empty…
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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, I want to use the `PR-AUC` (or `ROC-AUC`) metrics for a few-shot classification problem where the test data is imbalanced.
Therefore, I need the positive (yes) **probability** to calculate this…
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### Search before asking
- [X] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussion…
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### Describe the issue linked to the documentation
Hi guys,
In the "ROC curve using micro-averaged OvR" part of the doc (https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html#r…
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[This paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4189457) is connected to the new minister of communications ([Sattar Hashemi](https://x.com/HashemiSattar)) in Iran: https://x.com/ircf…
irgfw updated
3 weeks ago
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This is a follow-up to the issue raised in https://github.com/scikit-learn/scikit-learn/issues/29554. However, I recall other issues raised for CV estimator in general.
So the context is the follow…
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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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# Building a multiclass classification model | Practical Cheminformatics
Data cleaning, adding structures to PubChem data, building a multiclass model, dealing with imbalanced data
[https://patwalte…
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### Deep Learning for Imbalance Classificaition
#### Survey
1. [A systematic study of the class imbalance problem in convolutional neural networks
Cost-Sensitive](https://arxiv.org/pdf/1710.05381.p…