softmax: softmax function

In deepNN: Deep Learning

softmax function

Description

A function to evaluate the softmax activation function, the derivative and cost derivative to be used in defining a neural network. Note that at present, this unit can only be used as an output unit.

Usage

softmax()

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, smoothReLU, ident

Examples

# Example in context

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

deepNN documentation built on Aug. 25, 2023, 5:14 p.m.