Dense layers are fully connected layers of neurons, meaning each neuron is connected to each other in the previous layer by a weighted synapse. The weights can be initialized by a user specified Initializer. The majority of the parameters in a standard feedforward network are contained within Dense layers.


# Param Default Type Description
1 neurons None int The number of neurons in the layer.
2 weight initializer He object The initializer of the weight parameter.
3 bias initializer Constant object The initializer of the bias parameter.


use Rubix\ML\NeuralNet\Layers\Dense;
use Rubix\ML\NeuralNet\Initializers\He;
use Rubix\ML\NeuralNet\Initializers\Constant;

$layer = new Dense(100, new He(), new Constant(0.));