Loss Functions

Common loss function are listed below. See the page

Neuralnet Alphabet⁠

for notation and meanings of symbols. And m below is the number of neurons in output layer.

MAE

Mean Absolute Error. This is not a good function, it’s not smooth.

⁠

Mean Squared Error. This loss function is common and good for regression, but can be used in classification too.

⁠

Cross-Entropy. This loss function can work with both sigmoid and softmax activations.

For more maths, see:

https://gombru.github.io/2018/05/23/cross_entropy_loss/⁠

⁠

Categorical Cross-Entropy. This loss function is common and good for classification; this loss function should work with softmax activation only.

For more maths, see:

https://gombru.github.io/2018/05/23/cross_entropy_loss/⁠

⁠

Want to print your doc?
This is not the way.

Try clicking the ⋯ next to your doc name or using a keyboard shortcut (

CtrlP

) instead.