How could I cancel pre-processing and post-processing stages when training a neural network?
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Whenever I use fitnet it applies minmax to my data by default, however my data is already scaled, so I was just wondering if there was a way to change this default feature.
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Greg Heath
2016-10-3
To remove mapminmax as a processFcn but still keep removeconstantrows
close all, clear all, clc
% WITH DEFAULT MAPMINMAX
[x,t] = simplefit_dataset;
net = fitnet;
rng(0)
[net tr y e ] = train(net,x,t);
NMSE1 = mse(e)/mean(var(t',1)) % 1.7558e-05
% WITHOUT DEFAULT MAPMINMAX
[x,t] = simplefit_dataset;
net = fitnet;
net.inputs{1}.processFcns={'removeconstantrows'};
net.outputs{2}.processFcns={'removeconstantrows'};
rng(0)
[net tr y e ] = train(net,x,t);
NMSE2 = mse(e)/mean(var(t',1)) % 1.7241e-05
Hope this helps.
Thank you for formally accepting my answer
Greg
2 个评论
Alexandra Ntemourtsidou
2016-10-4
Greg Heath
2016-10-5
Yes. The first statement is for inputs and the second for outputs.
If you do not want to eliminate constant rows, use '' for the RHS (maybe {} will work also)
Hope this helps.
Greg
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