Source

Dropout#

Dropout is a regularization technique for reducing overfitting in neural networks by preventing complex co-adaptations on training data. It works by temporarily disabling neurons during each training pass. It also is a very efficient way of performing model averaging with neural networks.

Parameters#

# Param Default Type Description
1 ratio 0.5 float The ratio of neurons that are dropped during each training pass.

Example#

use Rubix\ML\NeuralNet\Layers\Dropout;

$layer = new Dropout(0.2);

References#

  • N. Srivastava et al. (2014). Dropout: A Simple Way to Prevent Neural Networks from Overfitting.