Dense Layer

This module belongs the 'TensorFlow API' category .

Description

The Dense Layer module in a neural network is a layer that performs the integration of the input along with an activation.

Parameters

The Dense Layer module contains an enriched set of functions to configure at will.

There are many types of activation functions in the Dense Layer module.

We can , for instance, set the Tensorflow Keras API as either:

• Automatic,

• Sequential

• or Functional.

Activation function

The Activation function, in turn, could be :

• Sigmoid

• Softmax

• Exponential linear unit (ELU)

• Scaled Exponential Linear Unit (SELU)

• Softplus

• Softsign

• Rectified Linear Unit(RELU)

• Hyperbolic tangent

• Sigmoid Hard

• Sigmoid Exponential (base e)

• Identity function (Linear)

Input

As an input we can choose among : dimension, shape and batch input shape.

Initialization

Both Kernel and Bias can be attributed an initialization based on :

• Zeros

• Ones

• Constant

• Random

• Normal

• Random Uniform

• Truncated Normal

• Variance scaling

• Orthogonal

• Identity

• Le Cun Uniform

• Glorot Normal

• He Normal

• Le Cun Normal

• He Uniform

Regularizers are available: bias , activity , kernel .

Activity regularizer: None, L1 regularizer, L2 regularizer