How can I continue training with additional data to an already existed neural network?
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Lamesginew
el 9 de Oct. de 2014
Editada: Roberto de Freitas Cabral
el 30 de Ag. de 2018
I have a trained neural network with some data set, let A. That is, the network is trained on data set A. Later on, I want to train this network which is trained on data set A with some additional data set, let B. I think, making together data set A and B, and then training the network is possible. But, what I want is not training for the merged data set, rather continue training on the existed trained network for data set B only. Any help for this... contact me via lame2002@gmail.com. Thanks,
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Greg Heath
el 10 de Oct. de 2014
In general, this technique will not work if you want to preserve good performance on A.
If you don't want to use all of A, use a subset that exemplifies the basic characteristics of A.
There is a huge history of NN forgetting. Don't waste your time with your original idea.
Spend your time thinking about how to find that characterization subset. Unsupervised clustering of A is one idea. Then use the A cluster centers with B.
Hope this helps.
Thank you for formally accepting my answer
Greg
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Roberto de Freitas Cabral
el 30 de Ag. de 2018
Editada: Roberto de Freitas Cabral
el 30 de Ag. de 2018
Although I'm new to neural networks and MATLAB, I had the same question recently.
Searching the web, I've found an interesting link that certainly has to do with your question: https://www.mathworks.com/help/nnet/ug/neural-network-training-concepts.html
I hope it helps.
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