net reusing
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Luca Cavazzana
am 13 Dez. 2011
Beantwortet: Greg Heath
am 17 Feb. 2014
Hi, I'm creating a set of nets using a code more or less like this:
net = patternnet(10);
% net initialization
% ...
for ii=1:10
net = train(net,in,tar);
netSet{ii} = net;
end
What I see is the first training takes relatively a lot of time, while the others usually are far faster. So a question comes to my mind: could be each new training starts from the previous net? If so, is there a function to re-randomize the initial weights (without the need to allocate a new net)?
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the cyclist
am 13 Dez. 2011
Inside your loop, the input to train() is definitely the value of "net" that just calculated in the previous. I am guessing you want to do something like this instead:
net0 = patternnet(10);
% net0 initialization
% ...
for ii=1:10
net = train(net0,in,tar);
netSet{ii} = net;
end
This way, you are starting from the initialized value "net0" each time. I don't know enough about neural nets to know if train() has some randomness in it that will make each value of netSet(ii) different.
Also, note that you do not really need the intermediate value "net" inside your loop. You could just do
for ii=1:10
netSet{ii} = train(net0,in,tar);
end
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Greg Heath
am 16 Dez. 2011
Patternnet is selfinitializing. Therefore
1. Initialize the rand RNG
2. Create an outer loop over nH number of candidate values for H, the number of hidden nodes
3. Create an inner loop of Ntrials random initialization designs.
4. Bottom Line: Each of the nH*Ntrials designs begins with a different set of initial weights.
Hope this helps.
Greg
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Greg Heath
am 18 Dez. 2011
No, weight randomization only occurs when the net is created
( e.g., net = newff(...))
Greg
Greg Heath
am 18 Dez. 2011
No, weight randomization only occurs when the net is created
( e.g., net = newff(...))
Greg
Greg Heath
am 17 Feb. 2014
With the current set of net creation functions ( e.g., fitnet, patternnet, feedforwardnet,...) weight initialization does not occur at net creation.
If weights have not been assigned, they will be automatically initialized by train. Otherwise, train will just use the existing weights.
Therefore, when designing multiple nets in a loop, the function configure must be used to initialize the nets at the top of the loop before train is called.
net = configure(net, x, t);
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