# 0-1 Loss Function

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A 0-1 Loss Function is a bounded loss function that ...

**Counter-Example(s):****See:**Convex Loss Function, Decision Theory, Indicator Notation.

## References

### 2015

- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/loss_function#0-1_loss_function Retrieved:2015-1-7.
- In statistics and decision theory, a frequently used loss function is the
*0-1 loss function*: [math]L(\hat{y}, y) = I(\hat{y} \ne y), \, [/math]

where [math]I[/math] is the indicator notation.

- In statistics and decision theory, a frequently used loss function is the

### 2009

- (Gentle, 2009) ⇒ James E. Gentle. (2009). “Computational Statistics." Springer. ISBN:978-0-387-98143-7
- QUOTE: Any strictly convex loss function over an unbounded interval is unbounded. It is not always realistic to use an unbounded loss function. A common bounded loss function is the 0-1 loss function, which may be : [math]L_{0−1}(θ, a) = 0 \ \text{if} \mid g(θ)−a \mid ≤ α(n)[/math] : [math]L_{0−1}(θ,a)=1 \ \text{otherwise}.[/math]