More performance metrics
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- Dominant language
- R
- Stars
- 46
- Forks
- 15
- PR merge metrics
- No merged PRs in 30d
Description
My understanding of v1.1 on CRAN is that only 1 performance metrics is implemented for regression (mean absolute error?) and classification (overall accuracy?). It would be great to implement more metrics like:
Numeric outcomes
- R-squared
- mean absolute error
Binary outcomes
- AUC
- PRAUC
- F1
- sensitivity
- specificity
- PPV
- NPV
- Matthew's correlation coefficient
3+ category outcomes
- "one-vs-all" versions of all of the binary metrics, as well as the average across classes
Contributor guide
No contributing guide indexed for this repository
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
Start by locating the existing regression and classification performance-metric entry points in the v1.1 implementation. Review how the current metric is exposed and tested, then determine how the requested numeric, binary, and one-vs-all multiclass metrics should fit that structure. Done means the listed metrics are implemented with coverage for multiclass averages.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100