Data and feature engineering · MLD-0255
Data augmentation
Creating modified training examples intended to preserve relevant targets.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Randomly crop training images.
Original caveat
Augmentations must respect the task's label semantics.
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 ↗