Provide out-of-the-box statistical inference support
Open
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evaluation
- Dominant language
- Python
- Stars
- 314
- Forks
- 77
- Avg merge
- 4d 6m
- Merged PRs (30d)
- 10
Description
It will make it easier to use LensKit effectively if we automate support for standard or widely-accepted inferences:
- pairwise t-tests (with and without correction)
- confidence intervals on model performance
- effect sizes and associated confidence intervals
Supporting Bayesian inference will be a separate ticket.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. First locate the existing model-performance evaluation APIs and tests, then scope support for pairwise t-tests, corrected and uncorrected comparisons, confidence intervals, and effect sizes with associated intervals; Bayesian inference is explicitly out of scope.
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