engineering-features-for-machine-learning
Create, encode, transform, and select features before model fitting. Use when the user needs feature engineering decisions or implementation, not final training ownership or leakage auditing.
npx skills add majiayu000/claude-skill-registry --skill engineering-features-for-machine-learning --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Feature Engineering Toolkit Use this skill when the main question is how to improve or restructure the input features. ## Overview This skill covers feature creation, encoding, scaling coordination, and feature selection before the model is finalized. ## When to Use This Skill - Creating derived variables, interaction terms, bins, encodings, or date-based features - Selecting or pruning features before training - Reworking feature representations to fit model assumptions or data geometry ## Not For / Boundaries - Full training runs and benchmark ownership: use `training-machine-learning-models` - Post-hoc interpretation of a trained model: use `feature-importance-analyzer` - Leak checking across the preprocessing order: use `ml-data-leakage-guard` ## Typical Outputs - Candidate feature set changes - Implementation notes for encoders, scalers, and selectors - Rationale for what to keep, drop, or combine ## Related Skills - `data-normalization-tool` for scaling-only questions - `ml-data-leakage-guard` before accepting the engineered pipeline
- Overview
- When to Use This Skill
- Not For / Boundaries
- Typical Outputs
- Related Skills
What does the engineering-features-for-machine-learning skill do?
Create, encode, transform, and select features before model fitting. Use when the user needs feature engineering decisions or implementation, not final training ownership or leakage auditing.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill engineering-features-for-machine-learning --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.