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Noorain drift detection #5
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…training.py and not from main.py
…on storage as parquet file with one target column and 36 predictions step-wise
…orecasts in that particular run
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I'm holding off on reviewing this PR since it builds upon the baseline and ensemble branches, which need to be finalized first. It's apparent that this PR is dependent on prior work, but differentiating it from the existing baseline and ensemble PRs would require a significant investment of time—likely an hour or more. Considering there are already identified issues within those foundational PRs, diving into this new PR would not be the most efficient use of our time at the moment.
To streamline our review process and ensure we're working as effectively as possible, I recommend the following steps:
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Resolve Existing Issues: Please prioritize addressing and resolving any outstanding issues in the baseline and ensemble branches. This will provide a clear and stable foundation for any additional work.
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Separate Branches for Separate Features: Moving forward, ensure that new features or projects are developed on new branches created from the main branch. This will help in keeping our codebase organized and making the review process more manageable.
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Update on Resolution: Once the issues in the baseline and ensemble PRs have been addressed, let me know. We can then revisit this PR with a clearer understanding of its unique contributions and changes.
By focusing on these steps, we'll maintain a clean and efficient workflow, ensuring that each part of the project is reviewed thoroughly and integrated seamlessly.
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Not gonna comment on the PR as it builds on your baseline and ensemble branches. These need to be in order first. I recognize that this PR is inherently one that builds on your branch, but it would take me an hour or so at least to figure out the difference between this and the two other PR - and since there are a number of this that needs to be fixed in those, it would not be a prudent use of time right now
drift detection for mean ensemble and step_6