defining divideblock function for feedforward net

i've used 'divideblock' function as follow:
net.divideFcn = 'divideblock'; net.divideParam.trainRatio = 0.6; net.divideParam.valRatio = 0.20; net.divideParam.testRatio = 0.20;
for feedforward neural network. when i run the program, the details of the network will be displayed. the problem is, it display 2 neural network details. the first set will show
net =
Neural Network
. . . .
functions:
adaptFcn: 'adaptwb'
adaptParam: (none)
derivFcn: 'defaultderiv'
divideFcn: 'dividerand'
and the other one shows
functions:
adaptFcn: 'adaptwb'
adaptParam: (none)
derivFcn: 'defaultderiv'
divideFcn: 'divideblock'
divideParam: .trainRatio, .valRatio, .testRatio
. . . .
is it suppose to be like this when we define 'divideblock' as a divide function? i expect it to display only 1 and not both, since i dont need my data to be randomized.
thank you. :)

1 个评论

Post your code.
P.S. Use fitnet for regression and patternnet for classification. Both call feedforwardnet and provide better output info. There is no reason to use feedforwardnet.

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 采纳的回答

The default 'dividerand' exists at net creation: net = fitnet(H)
Specifying 'divideblock' then replaces it.

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