cv-per-class-soft-f1-threshold-fitting
cv-per-class-soft-f1-threshold-fitting is a Model training & evaluation skill for AI agents, published by wenmin-wu in the ds-skills repository on GitHub. Skillspace rates cv-per-class-soft-f1-threshold-fitting D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Optimize per-class decision thresholds for macro-F1 by replacing the non-differentiable hard threshold with a sigmoid-sharpened soft-F1 surrogate and fitting the per-class threshold vector via least-squares — averaged over multiple random validation splits to suppress overfitting on rare classes
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 52
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 1 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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