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Re: Neural Network  Incremental Training
Posted:
May 29, 2014 5:46 AM


"Marko Kolarek" <kolarek@gmail.com> wrote in message <lm4ms9$ejq$1@newscl01ah.mathworks.com>... > "George Xu" <gxu5@jhu.edu> wrote in message <ef314ef.1@webx.raydaftYaTP>... > > Thank you for your input Greg. I'll give this a shot. > > > > Thanks again! > > > > Greg Heath wrote: > > > > > > > > > George Xu wrote: > > >> Hello, > > >> > > >> I would like to use the Neural Network module to train a > > network > > > that > > >> can be used as a classifier. At a later time when additional > > data > > > is > > >> available, train the network further using the new data but > > > without > > >> training everything else again. > > >> > > >> Is there a way to load an existing network, perform the > > training, > > > and > > >> add the weights from the new training to the existing network? > > > > > > You have to > > > > > > 1. Prevent the network from "forgetting the old data" by saving > > > a Calibration Set which will be combined with the new data > > > when the net is retrained. > > > 2. Decide on the relative weighting of the old and new data. > > > > > > The best way is to use an RBF (help newrb). However, you might > > > run into the problem of having more estimated parameters than > > > you have training equations (Neq = Ntrn*O = product of number > > > of training cases and number of network outputs). You then have > > > to write some original code to do one or more of the following > > > > > > 1. Remove some redundant RBFs > > > 2. Merge some neighboring RBFs > > > 3. Determine the output layer weights using pinv. > > > > > > I think you can do 3 by modifying newrb. > > > > > >> My current implementation, which does not seem to work is as > > > follows: > > >> > > >> load Oldnet > > >> [NewNet, tr] = train(OldNet, features) > > > > > > Aha! The classical "plasticity/stability dilema" which should have > > > been named "plasticity/stability tradeoff". If you stick with an > > > MLP > > > (help newff) I can't think of a good fix. > > > > > >> Any help would be greatly appreciate it. > > >> > > >> Thanks! > > > > > > The problem is solvable. However, it will take a good understanding > > > of the newrb source code before you can begin to deal with > > > mitigating the overfitting problem of more parameters to > > > estimate than you have training equations. > > > with new data. > > > > > > Good Luck. > > > > > > Greg > > > > > > > > I am sorry to be reviving this old thread, but could you please tell me have you come up with a solution?
I have described the solution above and coded tens of versions in Fortran from 1983 to 1998. However, they were government sponsored and are not available.
A postretirement MATLAB version in 2004 was lost in a computer crash. I have no desire to try to reconstruct it.



