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Claude-skill-registry feature-engineering-kit

Auto-generate features with encodings, scaling, polynomial features, and interaction terms for ML pipelines.

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/feature-engineering-kit" ~/.claude/skills/majiayu000-claude-skill-registry-feature-engineering-kit && rm -rf "$T"
manifest: skills/data/feature-engineering-kit/SKILL.md
source content

Feature Engineering Kit

Automated feature engineering with encodings, scaling, and transformations.

Features

  • Encodings: One-hot, label, target encoding
  • Scaling: Standard, min-max, robust scaling
  • Polynomial Features: Generate interactions
  • Binning: Discretize continuous features
  • Date Features: Extract time-based features
  • Text Features: TF-IDF, word counts
  • Missing Value Handling: Imputation strategies

CLI Usage

python feature_engineering.py --data train.csv --output engineered.csv --config config.json

Dependencies

  • scikit-learn>=1.3.0
  • pandas>=2.0.0
  • numpy>=1.24.0