Better handling of changes in imputation rules
- Dominant language
- Jupyter Notebook
- Stars
- 201
- Forks
- 62
- PR merge metrics
- No merged PRs in 30d
Description
The current imputation structure makes the imputation rules part of the variable definition, which may give rise to two problems:
* If you want to experiment with imputation rules, changing them currently won't generate a distinct model group without specifying the difference in user metadata, which is error-prone
* Changes to imputation rules won't cause the features table to be rebuilt (this is also true of general changes to feature definition) if `replace` is set to False, so would need to either be run with `replace=True` or with manually deleting the affected features tables.
Contributor guide
Research direction
No files, tests, or entry points are named. Trace how imputation rules are stored in variable definitions and how model groups and feature tables detect changes; the work is done when changing rules creates a distinct model group and rebuilds affected feature tables when replace is false.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100