smoothReLU {deepNN}R Documentation

smoothReLU function

Description

A function to evaluate the smooth ReLU (AKA softplus) activation function, the derivative and cost derivative to be used in defining a neural network.

Usage

smoothReLU()

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, ReLU, ident, softmax

Examples


# Example in context

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


[Package deepNN version 1.2 Index]