deepNN (version 1.2)

ReLU: ReLU function

Description

A function to evaluate the ReLU activation function, the derivative and cost derivative to be used in defining a neural network.

Usage

ReLU()

Value

a list of functions used to compute the activation function, the derivative and cost derivative.

References

1. Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach. Deep Learning. (2016)

2. Terrence J. Sejnowski. The Deep Learning Revolution (The MIT Press). (2018)

3. Neural Networks YouTube playlist by 3brown1blue: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi

4. http://neuralnetworksanddeeplearning.com/

See Also

network, train, backprop_evaluate, MLP_net, backpropagation_MLP, logistic, smoothReLU, ident, softmax

Examples

# Example in context

net <- network( dims = c(100,50,20,2),
                activ=list(ReLU(),ReLU(),softmax()))