Comments (2)
ajratner
commented on June 29, 2024
There are at least two dimensions:
- Efficacy: this is new ground for data programming and very exciting- how do we best get users to iterate so as to efficiently and effectively improve quality?
- Correctness / generalization: how do we push best practices for e.g. not developing and testing on the same holdout set, etc?
This will be a longer term question... but in the shorter term, @jason-fries we should all discuss together how to do this most properly for the hackathon / in the bio setting
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henryre
commented on June 29, 2024
- (+) best practices for learning
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Related Issues (20)
- How do we get coefficients for the interactions of 2 labeling functions? HOT 2
- Upgrade numpy from <=1.20.0 to 1.21.5 to support M1 Macs HOT 2
- No LF for negative class in NER/ high LF overlap HOT 1
- When a token does not fall under any of the class labels or abstains in NER? HOT 2
- Support for M1 Mac HOT 6
- Spacy v3 support HOT 11
- When will snorkel officially releases 0.9.9 version on conda? HOT 8
- What prevent the machine learning model from overfiting to the labeling function? HOT 5
- Overlap and conflict rate between all labeling functions (LFs) HOT 6
- AttributeError: split not found HOT 3
- Update documentation to emphasize the need to avoid broad LabelingFunctions for LabelModel HOT 3
- probabilistic weight for each labelling function? HOT 2
- ModuleNotFoundError: No module named 'snorkel.learning',how to solve it? HOT 1
- Dependency need update HOT 3
- How the label model works HOT 4
- labeling_function as a method on class HOT 2
- Can I use Snorkel for multi-label problems ? HOT 2
- Concept Question HOT 6
- Snorkel Coral for melanoma sementation classification HOT 1
- getting negative value after label_model.get_conditional_probs() and snorkel LF HOT 1
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