Jacobian creation technique in Neural Network (NN)
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I am working with an NN and I am trying to make a Jacobian (a new one by getting the differential values)of dy/dw, where 'y' is the output of the network and 'w' is the weights or bias parameters of the network.
Well, originally MatLab also creates a Jacobian as same as mine (while a NN is being trained), but values of my Jacobian and the values from MatLab Jacobian are different.
So i found out that when I disabled the 'mapminmax' function on inputs and outputs, both Jacobians have same results, but when they are enabled the values are different. But i need to keep 'mapminmax' switched on to have good results from the NN.
So can anyone please tell me what MatLab code does as an extra work on their Jacobian when the 'mapminmax' function is imposed on inputs and outputs of the NN.
Please be kind enough to help I am trying to figure out this since several weeks.
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Akzeptierte Antwort
Greg Heath
am 15 Okt. 2012
I cannot access the current source code.
>> help nntraining.perfs_jejj
Copyright 2010 The MathWorks, Inc.
TODO - if no memory split, return intermediate variables
if their output arg is present.
>> doc nntraining.perfs_jejj
>> type nntraining.perfs_jejj
Error using type
File 'nntraining.perfs_jejj' not found.
====================================================
Try an older version that might not be considered proprietary
Hope this helps.
Greg
Thank you for formally accepting my answer.
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