Using Neural Network for data interpolation
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I am working on a research project that involves interpolating known Monte Carlo data to approximate data for unknown parameters. The known data is in the form of a 1750x3 array of independent variables (1750 sets of atomic number, electron energy, and depth) and a 1750x1 array containing 1750 samples of the charge deposited in the material. I used nftool to create and train a network using these data sets and the resulting network does not approximate the data at all.
In the image above, the blue line is a plot of charge deposition vs depth of the actual data, while the red line is the output of the neural network when the independent variables corresponding with the blue line data are input (so they should be exactly the same). I have tried training the network with a large array of hidden neurons. I'm a physics major, not compsci, so I know next to nothing about why this would happen/how to fix it.
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Greg Heath
on 8 Oct 2015
Use the command line approach
help FITNET
doc FITNET
Search the NEWSGROUP and ANSWERS using subsets of
greg fitnet tutorial
Hope this helps.
Greg
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