Relative Entropy#
Relative Entropy (or Kullback-Leibler divergence) is a measure of how the expectation and activation of the network diverge. It is different from Cross Entropy in that it is asymmetric and thus does not qualify as a statistical measure of error.
Parameters#
This cost function does not have any parameters.
Example#
use Rubix\ML\NeuralNet\CostFunctions\RelativeEntropy;
$costFunction = new RelativeEntropy();
Last update:
2021-01-25