hyptan {deepNN} | R Documentation |
hyptan function
Description
A function to evaluate the hyperbolic tanget activation function, the derivative and cost derivative to be used in defining a neural network.
Usage
hyptan()
Value
a list of functions used to compute the activation function, the derivative and cost derivative.
References
Ian Goodfellow, Yoshua Bengio, Aaron Courville, Francis Bach. Deep Learning. (2016)
Terrence J. Sejnowski. The Deep Learning Revolution (The MIT Press). (2018)
Neural Networks YouTube playlist by 3brown1blue: https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
http://neuralnetworksanddeeplearning.com/
See Also
network, train, backprop_evaluate, MLP_net, backpropagation_MLP, ReLU, smoothReLU, ident, softmax
Examples
# Example in context
net <- network( dims = c(100,50,20,2),
activ=list(hyptan(),ReLU(),softmax()))
[Package deepNN version 1.2 Index]