Data and feature engineering · MLD-0257
Data curation
Selecting, checking, cleaning, and organizing data for a defined purpose.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Remove unusable examples before model training.
Original caveat
More aggressive filtering can reduce useful diversity.
Context and aliases
Level: Intermediate. Stages: Data · Training · Evaluation.
Tags: ML · DL · SLM · LLM.
Aliases: None recorded.
Related concepts
Concepts linking here
Original references
- scikit-learn: cross-validation ↗ · Reference link
- scikit-learn: missing-value imputation ↗ · Reference link
- scikit-learn: preprocessing ↗ · Reference link
- scikit-learn: feature selection ↗ · Reference link
- Original reference URL ↗