'apply' 'reverse' in mapminmax

8 vues (au cours des 30 derniers jours)
nguyen tien
nguyen tien le 25 Mar 2016
Modifié(e) : KAE le 9 Oct 2018
hi everyone, what are 'apply' and 'reverse' in mapminmax function in neuron network? if i dont use them in mapminmax, why result in ouputs neuron network is different.
p = [0, 1, 2, 3, 4, 5, 6, 7, 8];
t = [0, 0.84, 0.91, 0.14, -0.77, -0.96, -0.28, 0.66, 0.99];
nneuron = 5;
net = feedforwardnet(nneuron);
net.inputs{1}.processFcns{2} = 'mapminmax';
net.outputs{2}.processFcns{2} = 'mapminmax';
net = configure(net, p, t);
net.trainParam.epochs = 50;
net.trainParam.goal = 0.01;
net = train(net, p, t);
y1 = sim(net, p)
pn = mapminmax('apply', p, net.inputs{1}.processSettings{2});
y2n = mySigmoidalNetwork(pn, net, nneuron);
y2 = mapminmax('reverse', y2n, net.outputs{2}.processSettings{2})
function out = mySigmoidalNetwork(in, net, nneuron) Nin = length(in);
IW = net.IW{1,1};
B1 = net.b{1};
b1 = B1(1);
LW = net.LW{2,1};
b2 = net.b{2};
h = tansig(IW*in+B1*ones(1,Nin));
out = LW*h + b2;

Réponses (1)

KAE
KAE le 9 Oct 2018
Modifié(e) : KAE le 9 Oct 2018
mapminmax is a scaling that is applied to your input data to make it in the [-1,1] range, which you want to do. Then 'reverse' can undo the scaling, which is actually done automatically if you use your net to estimate results. If you don't apply the scaling on the inputs (which you should have a good reason not to do), you will get different results. There is a lot of information on scaling here .

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by