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Hi just wanted to ask if the multimodal predictor in AutoGluon handles imbalanced datasets automatically? Thanks!
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![image](https://github.com/user-attachments/assets/836bb753-191b-447c-b515-c89aad887320)
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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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# max_delta_step
https://xgboost.readthedocs.io/en/latest/tutorials/param_tuning.html
https://xgboost.readthedocs.io/en/latest/parameter.html
![image](https://user-images.githubusercontent.com/…
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Dear Scimap Team,
Thank you for your exceptional work in advancing spatial-omics biology. I am currently facing a challenge with integrating two different scales of CODEX quantification data proc…
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Imbalanced dataset is relevant primarily in the context of supervised machine lea…
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Are the shap values in the summary plot affected by an imbalanced dataset? More in general, are shap values affected in such cases?
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Hello! Very interesting paper! I am curious about trying this method out but I wanted to ask a couple questions first:
1. Based on your supplemental table 1, you show the number of cells coming …
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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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Hi,
I'm working on a multiple class detection with imbalanced training data, which means the distribution of images on each class is far from uniform. Any part of code in AlexeyAB repository could s…