Hinge loss
Hinge loss is a classification loss that penalizes predictions whose signed margin falls below a specified threshold, typically increasing with the shortfall.
Math and Architectures of Deep Learning
A classification loss that is zero once a margin criterion is satisfied and increases only when incorrect classes score too close to or above the correct class.
- How it is used
- Uses classification scores to stop optimization once the correct class is sufficiently favored over incorrect classes.
- How deep it goes
- Defines the multiclass SVM formula, margin, and zero-versus-positive cases through score comparisons.
- Examples
- Uses cat, dog, airplane, and automobile scores to illustrate correct-versus-incorrect class comparisons and good or bad outputs.
- What you can do after
- Evaluate classification scores by identifying margin violations and recognizing when hinge loss becomes zero.
Read how Math and Architectures of Deep Learning explains hinge loss →
Machine Learning Algorithms in Depth
A hinge loss function penalizes classification examples whose signed margin falls below a specified threshold.
- How it is used
- Connects perceptron classification to stochastic-gradient optimization through a margin-based loss.
- How deep it goes
- Derives signed margins, nondifferentiability, subgradients, and parameter updates, stopping before a separate SVM treatment.
- Examples
- Uses an iris perceptron implementation and compares hinge loss with 0–1 loss and log-loss.
- What you can do after
- Apply it via stochastic gradient descent to understand and reproduce perceptron parameter updates.
Read how Machine Learning Algorithms in Depth explains hinge loss →
Related concepts
- loss functionkind of · A loss function is a mathematical measure of a model’s prediction error or other undesirable behavior relative to a target or objective.
- cross entropy losscontrasts with · Cross-entropy loss measures the expected negative log probability that a predicted distribution assigns to outcomes drawn from a target distribution.
- marginhas part · A classification margin measures separation or confidence, expressed as distance from a decision boundary or as the correct class's score advantage over competing classes.
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