Losses and objectives · MLD-0362
Empirical risk minimization
Selecting a model to minimize loss on observed training data.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Fit a classifier by average cross-entropy.
Original caveat
Minimizing training loss alone can overfit.
Context and aliases
Level: Intermediate. Stages: Theory · Training · Evaluation.
Tags: ML · DL · SLM · LLM.
Aliases: ERM.
Related concepts
Concepts linking here
Original references
- Deep Learning: online textbook ↗ · Consulted
- scikit-learn: evaluation metrics ↗ · Reference link
- PyTorch neural-network layers ↗ · Reference link
- Original reference URL ↗