Losses and objectives · MLD-0124
Binary cross-entropy
Cross-entropy for binary targets and predicted probabilities.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Train independent multilabel outputs.
Original caveat
Stable implementations often accept logits, not probabilities.
Context and aliases
Level: Intermediate. Stages: Theory · Training · Evaluation.
Tags: ML · DL · SLM · LLM.
Aliases: BCE · binary log loss.
Related concepts
Original references
- Deep Learning: online textbook ↗ · Consulted
- scikit-learn: evaluation metrics ↗ · Reference link
- PyTorch neural-network layers ↗ · Reference link
- Original reference URL ↗