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- [x] delete the one we have now in slips repo
- [ ] re-do the module
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Hi
First of all - thanks for making this extremely useful extension available.
I have installed the app without issues and ran it on my own trained nnUNet. It works very well. I just have a ques…
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Hello!
If I have two trainers (say two different losses) -- How would I go about ensembling them for inference?
Basically, get the ensemble of all the folds for each trainer (which usually happens…
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📚 This guide explains how to use YOLOv5 🚀 **model ensembling** during testing and inference for improved mAP and Recall. UPDATED 25 September 2022.
From https://www.sciencedirect.com/topics/comput…
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### Discussed in https://github.com/openvinotoolkit/anomalib/discussions/1131
Originally posted by **blaz-r** June 15, 2023
## Project abstract
When detecting defects in high-resolution im…
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It would be useful to allow the user to run true cross-validation out of the box in TabularPredictor.
True cross-validation would ensure that the validation data is never used for any early stoppin…
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Right now the submission takes ~45 minutes to score on 31 days of data, so we have ~4.5 hours to spare which means we have time to do some blending/ensembling. I think it’d be good if we had one or mo…
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consider all the ones listed at:
http://mlwave.com/kaggle-ensembling-guide/
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Untrained & trained ensembles. cmu-delphi/exploration-tooling has work on ad-hoc approach to untrained ensemble. tidymodels also has some stacking framework which might or might not be applicable. …
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### Description
Often, some pipelines require the ensembling of different statistical models. We can accomplish this by introducing a new module in the library named `statsforecast/ensembles.py`, whi…