softmax
Soft max transfer function
Graph and Symbol
Syntax
A = softmax(N,FP)
Description
softmax is a neural transfer function. Transfer functions calculate a
layer’s output from its net input.
A = softmax(N,FP) takes N and optional function
parameters,
N |
|
FP | Struct of function parameters (ignored) |
and returns A, the S-by-Q matrix
of the softmax competitive function applied to each column of N.
info = softmax(' returns information
about this function. The following codes are defined: code')
softmax('name') returns the name of this function.
softmax('output',FP) returns the [min max] output
range.
softmax('active',FP) returns the [min max] active
input range.
softmax('fullderiv') returns 1 or 0, depending on whether
dA_dN is
S-by-S-by-Q or
S-by-Q.
softmax('fpnames') returns the names of the function parameters.
softmax('fpdefaults') returns the default function parameters.
Examples
Here you define a net input vector N, calculate the output, and plot
both with bar graphs.
n = [0; 1; -0.5; 0.5];
a = softmax(n);
subplot(2,1,1), bar(n), ylabel('n')
subplot(2,1,2), bar(a), ylabel('a')
Assign this transfer function to layer i of a network.
net.layers{i}.transferFcn = 'softmax';
Algorithms
a = softmax(n) = exp(n)/sum(exp(n))