How can I combine multiple input-target sets in NARX Neural Network to improve general model performance?
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Hi there, I have been using he Neural Network Time Series toolbox to build models where I inset my 11 different inputs, and 1 output time series to produce a model. I have 6 sets of this data (let's call them A-F), and I would ultimately like to produce a model that is trained on all 6 sets of data.
Currently I am able to train a neural network on one site (e.g. A) and test on another site (e.g. B) - but to improve the model performance, I would like to train the model on e.g. 5 sets of data, and then test on 1 for validation purposes.
Any help would be gratefully received.
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christttttttophe
on 29 Jan 2020
Edited: christttttttophe
on 29 Jan 2020
Any answers on this?
Possibly divide mode would be sampletime?
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