LaTeX
L=-[y\log p+(1-y)\log(1-p)]Variables
- Define all variables, domains, and units before substitution.
How to use this formula
Measures probabilistic classification loss for a binary target.
Important notes
- Verify assumptions and conventions before use.
Quick example
Apply the binary cross entropy to a small known case and verify the result.
Applicability, worked calculation, and verification
Assumptions and domain checks
- Verify assumptions and conventions before use.
- Logarithm arguments must be positive in the real domain, and the base must be stated when it is not implied.
- State the data, loss, regularization, normalization, and optimization assumptions used by the model.
Worked example
Apply the binary cross entropy to a small known case and verify the result.
Common mistakes
- Before substituting values into Binary Cross Entropy, map each variable to its definition and preserve every sign, exponent, subscript, and grouping mark.
- Verify the result of Binary Cross Entropy with a known case, inverse operation, dimensional check, or independent calculation before publishing it.
Continue the workflow
Use Binary Cross Entropy in your own work
- Check the domainMatch the variables and assumptions to the problem before substituting values.
- Copy the exact notationPreserve grouping, signs, and exponents in
L=-[y\log p+(1-y)\log(1-p)]. - Edit or convertOpen the expression in the LaTeX editor, then export it for your document or web page.
Review and verification
Last reviewed: 2026-07-23
Automated quality check: Kept noindex until the missing evidence is supplied.
Formula references
- Digital Library of Mathematical FunctionsNational Institute of Standards and Technology — Definitions, notation, identities, and reference material for mathematical functions.
Frequently asked questions
What is the Binary Cross Entropy used for?
Measures probabilistic classification loss for a binary target.
Can I copy this formula as LaTeX?
Yes. Copy L=-[y\log p+(1-y)\log(1-p)] or open it in the LaTeX editor.
What should I check before using it?
Confirm that each variable, unit, domain restriction, and assumption matches the problem.