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Hyperparameters and accuracy for AtrialFibrillation dataset. #52

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letsGoBharat opened this issue May 11, 2023 · 2 comments
Open

Hyperparameters and accuracy for AtrialFibrillation dataset. #52

letsGoBharat opened this issue May 11, 2023 · 2 comments

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@letsGoBharat
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letsGoBharat commented May 11, 2023

Hello,

I am attempting to perform pre-training and fine-tuning on the AtrialFibrillation dataset, but I am unable to locate the hyperparameters and corresponding performance metrics in the relevant paper. Can you please provide me with this information, if available?

@letsGoBharat
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Is it possible to get some help with this? @gzerveas

@gzerveas
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Hi, this dataset was not included in the evaluation of the paper. If it is in the time series regression/classification archive, you can download it and put it in a directory as the README indicates, and the class TSRegressionArchive(BaseData): in the data.py should be able to handle it.
However, I can't really tell what would be good hyperparameters without having worked with this dataset. I suggest looking at the paper's table with default hyperparamters as a starting point, and experiment a bit (have a look at other datasets' hyperparameters to see which ones are the ones that most often affect performance). You may also consider using a sub-sample factor if the time series are very long or sampled with a high temporal resolution.

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