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Hello gents,
I was hoping I can get a second opinion about a situation I am facing while using setfit for a multi class classification use case.
The dataset is small with 255 samples across 9 clas…
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Hi, when fine-tuning the GigaPath on our own data, we run into the above error. Epoch 0 successfully runs, but get_metric fails. I'm not sure if this has to do with how the dataset.csv file is set up–…
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When it's important:
Classification problem, when function is a desired classification metric.
When applying to highly imbalanced problem, simple permutation will not preserve desired class ratios.
kaz94 updated
3 years ago
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### 🚀 The feature
For each classification datasets with balanced distribution on the classes (MNIST, CIFAR-N, etc...), it would be very useful to provide a standard dataset for the imbalanced versi…
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Thanks for maintaining the list of papers on long-tailed learning!
Our work : **SURE: SUrvey REcipes for building reliable and robust deep networks**[CVPR2024] addressed long-tailed distribution in …
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### pycaret version checks
- [X] I have checked that this issue has not already been reported [here](https://github.com/pycaret/pycaret/issues).
- [X] I have confirmed this bug exists on the [latest…
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### 🚀 The feature, motivation and pitch
The addition of weighted loss functions to the PyTorch library, specifically Weighted Mean Squared Error (WMSE), Weighted Mean Absolute Error (WMAE), and Weigh…
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**Is your feature request related to a problem? Please describe.**
I aims to run the lightgbm model for a multiclass classification problem. But I didn't find a feature parameter to balanced the data…
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The Glass + CH data has highly imbalanced SIC code classifications. The distribution of SIC Sections is shown below and this is more pronounced at the 4-digit level (some codes only have one example).…
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I had difficulties to implement different class weights in a multiclass classification. The proper way to set a class weight is in a dictionary but I can just use with parameters: Real, Integer and Ca…