What is log loss in classification?
Updated May 15, 2026
Short answer
Log loss measures classification model performance based on probability predictions.
Deep explanation
It penalizes confident wrong predictions heavily using cross-entropy formulation.
Real-world example
Used in Kaggle competitions for classification ranking.
Common mistakes
- Using hard labels instead of probabilities.
Follow-up questions
- Why is log loss better than accuracy?