classical-ml-pitfalls
classical-ml-pitfalls is a Model training & evaluation skill for AI agents, published by pvillega in the claude-templates repository on GitHub. Skillspace rates classical-ml-pitfalls D (59/100) and it passed the safety scan; the rating is based on static analysis only.
Deep classical-ML operational intuition — leakage taxonomy and Pipeline prevention, CV under non-IID rows, eval under imbalance (PR-AUC, MCC, threshold tuning), calibration, categorical encoding, boosted-tree footguns. Load when diagnosing too-good-to-be-true CV, non-IID CV design, calibration, threshold tuning, or boosted-tree config. Skip for deep-learning training (use `dl-training`), LLM eval, or forecasting (use `time-series-ml`). Triggers on: "target leakage", "group leakage", "GroupKFold", "StratifiedGroupKFold", "nested CV", "PR-AUC", "MCC", "threshold tuning", "Platt scaling", "CalibratedClassifierCV", "TargetEncoder", "ordered target statistics", "monotone_constraints", "TreeSHAP".
- Grade
- D
- Quality
- 59 / 100
- Safety
- Passed
- GitHub stars
- 23
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
- 84 / 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 0 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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