Try out categorical mode with xgboost (hashtag3817)

[vikramsubramanian]

See )

[mayil-ai[bot]]

Possible Solution

• Search the repository for issue or pull request number 3817 to find discussions or changes related to "categorical mode" in xgboost.
• If "categorical mode" is a new feature or a bug fix, look for a merge commit or pull request that references this issue number.
• Check the xgboost documentation or source code for any updates or parameters related to "categorical mode" that might have been introduced or modified.
• If "categorical mode" is a configuration parameter, ensure it is being passed correctly to the xgboost model training function.
• If there are any test cases related to "categorical mode," ensure they are updated to reflect the correct usage and expected behavior.
• If the issue is a bug, identify the root cause by tracing how "categorical mode" is used within the xgboost training process and fix the code accordingly.
• If the issue is a feature request, implement the necessary changes to support "categorical mode" in the xgboost training pipeline, ensuring compatibility with existing functionality.
• Verify that the solution works by running the software with "categorical mode" enabled and checking for the correct behavior or performance improvements.

Code snippets to check

bugbug → models → needsdiagnosis.py

This snippet imports xgboost and sets up a pipeline, which might need to be adjusted for categorical mode. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/needsdiagnosis.py#L1-L15

bugbug → models → rcatype.py

This snippet includes xgboost usage and a list of categories that might be relevant for the categorical mode. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/rcatype.py#L1-L52 This snippet defines an xgboost classifier within a pipeline and may need adjustments for categorical mode. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/rcatype.py#L56-L137

bugbug → models → defect.py

This snippet shows the use of xgboost with a pipeline, which could be relevant for implementing categorical mode. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/defect.py#L1-L21

bugbug → models → fixtime.py

This snippet imports xgboost and may require changes to support categorical mode. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/fixtime.py#L1-L21

bugbug → models → spambug.py

This snippet uses xgboost and may need to be reviewed for categorical mode compatibility. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/spambug.py#L1-L19

bugbug → models → tracking.py

This snippet includes xgboost and might be relevant for the issue if categorical mode affects the model. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/tracking.py#L1-L14

bugbug → models → assignee.py

This snippet uses xgboost and could be relevant if categorical mode needs to be tested or implemented. https://github.com/Mayil-AI/bugbug-21dec23/blob/0acd00da46afbb37bd047c0bce06ce7cfad21568/bugbug/models/assignee.py#L1-L29