🎉 Pipeline formalization, including scikit-learn block wrappers #101
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Review these changes at https://app.gitnotebooks.com/PLAID-lib/plaid/pull/101 |
Codecov Report✅ All modified and coverable lines are covered by tests. 📢 Thoughts on this report? Let us know! |
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@xroynard This PR contains additions in the dataset class (mainly a mechanism for calling slices of dataset, returning a dataset), and a first example of scikit-learn pipeline acting directly on plaid objects, in the examples/pipelines folder. To me, even if we change the design later, we can merge this PR for the modifications of datasets and since the pipeline are proposed as examples for the moment. edit: still working on it, marked as draft |
…e arg in PCAEmbeddingNode
…ing a global dict and specifying only arguments to be optimized by GridSearchCV (n_components of PCA for the moment)
…ents specified in config.yml
bstaber
reviewed
Jul 1, 2025
…GNS_FIELD_LOCATIONS
…meters and factorize FeatureIdentifier typing
bstaber
approved these changes
Aug 12, 2025
bstaber
approved these changes
Aug 13, 2025
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✨ Summary
This PR introduces significant improvements toward standardizing pipelines for the PLAID dataset, with a design that aligns closely with the scikit-learn API wherever applicable. It includes:
SampleandDatasetclasses to support these new features and ensure compatibility with the standardized pipeline interfaceThese changes pave the way for more modular, reusable, and interoperable components when building ML workflows on PLAID.