juniorCost Function
Difference between loss function and cost function
Updated May 15, 2026
Short answer
Loss is per sample error; cost is averaged over dataset.
Deep explanation
Loss function computes error for a single data point, while cost function aggregates losses over the entire dataset. In batch training, cost function guides parameter updates across all samples.
Real-world example
In spam detection, loss is per email, cost is over all emails.
Common mistakes
- Using terms interchangeably in strict mathematical contexts.
Follow-up questions
- Can loss and cost ever be identical?
- Why do we average cost?