ml-modeling
Best-practice suggestions for building, comparing, or reviewing predictive supervised ML models in Python with scikit-learn — Pipelines, ColumnTransformer, cross-validation, hyperparameter search, leakage prevention, candidate leaderboards, one-time held-out test evaluation, and threshold/loss-based decisions. Use for regression or classification; use statistical-modeling instead for coefficient inference and time-series-forecasting when row order and forecast horizon matter. Pair implementation reviews with code-review.
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- balintdecsi/skills
- Last source activity
- October 19, 2026 at 15:25
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- English
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SKILL.md
Source instructions · Read-only preview| name | ml-modeling |
|---|---|
| description | Best-practice suggestions for building, comparing, or reviewing predictive supervised ML models in Python with scikit-learn — Pipelines, ColumnTransformer, cross-validation, hyperparameter search, leakage prevention, candidate leaderboards, one-time held-out test evaluation, and threshold/loss-based decisions. Use for regression or classification; use statistical-modeling instead for coefficient inference and time-series-forecasting when row order and forecast horizon matter. Pair implementation reviews with code-review. |
