Neural Network Toolbox |
Mean absolute error performance derivative function
Syntax
dPerf_dE = dmae('e',E,X,PERF,PP)
dPerf_dX = dmae('x',E,X,PERF,PP)
Description
dmae
is the derivative function for mae
.
dmae('d',E,X,PERF,PP)
takes these arguments,
E
-- Matrix or cell array of error vector(s)
X
-- Vector of all weight and bias values
and returns the derivative dPerf/dE
.
dmae('x',E,X,PERF,PP)
returns the derivative dPerf/dX
.
Examples
Here we define E
and X
for a network with one 3-element output and six weight and bias values.
Here we calculate the network's mean absolute error performance, and derivatives of performance.
Note that mae
can be called with only one argument and dmae
with only three arguments because the other arguments are ignored. The other arguments exist so that mae
and dmae
conform to standard performance function argument lists.
See Also
dlogsig | dmse |
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