[source] # Dense Dense (or *fully connected*) hidden layers are layers of neurons that connect to each node in the previous layer by a parameterized synapse. They perform a linear transformation on their input and are usually followed by an [Activation](activation.md) layer. The majority of the trainable parameters in a standard feed forward neural network are contained within Dense hidden layers. ## Parameters | # | Name | Default | Type | Description | |---|---|---|---|---| | 1 | neurons | | int | The number of nodes in the layer. | | 2 | l2Penalty | 0.0 | float | The amount of L2 regularization applied to the weights. | | 3 | bias | true | bool | Should the layer include a bias parameter? | | 4 | weightInitializer | He | Initializer | The initializer of the weight parameter. | | 5 | biasInitializer | Constant | Initializer | The initializer of the bias parameter. | ## Example ```php use Rubix\ML\NeuralNet\Layers\Dense; use Rubix\ML\NeuralNet\Initializers\He; use Rubix\ML\NeuralNet\Initializers\Constant; $layer = new Dense(100, 1e-4, true, new He(), new Constant(0.0)); ```