Obtaining an analytical function of regression and Understanding the reversing concept of the normalisation (of input data) automatically done by Matlab Neural Network.

Question

Mohamed El Ibrahimi 2020-6-23

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/553111-obtaining-an-analytical-function-of-regression-and-understanding-the-reversing-concept-of-the-normal

关闭： MATLAB Answer Bot 2021-8-20

database.xlsx

I have a problem in understanding the reversing of the normalisation (of input data) automatically done by Matlab. I have followed the questions/answers presented in matworks.com website (using repmap, mapping and reverse mapping functions) but they does not work. if you can help me, this is my code:

entree=xlsread('........\database.xlsx',1); % inputsize=[24960    8]
sortie=xlsread('........\database.xlsx',2); % outputsize=[24960    1]
 n=6 ;
 net=fitnet(n); 
 [net,TR]=train(net,entree',sortie');
 %evaluation of the analytical function
  x=[ 1100 , 1155 , 10 , 1 , 0 , 0.7 ,  343.7508 , 1.00017 ];
  b1 = net.b {1};   %size=[4  1]
  b2 = net.b {2};    %size=[1  1]
  IW = net.IW {1,1};  %size=[4  8]
  LW = net.LW {2,1};   %size=[1  4]
  a1=IW*x'+b1;
  y=purelin(LW*(tansig(a1))+b2); %  comparison with net(x')~ 10.37error=abs(net(x')-y);

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

Mohamed El Ibrahimi 2020-6-25

编辑：Mohamed El Ibrahimi 2020-6-25

在 MATLAB Online 中打开

I have found the response to my question, we can find the right solution by mapping and reverse mapping

entree=xlsread('O:\Stage\database.xlsx',1);
sortie=xlsread('O:\Stage\database.xlsx',2);
entree=entree';
sortie=sortie';
N=length(sortie);
net=fitnet(n);
net.numLayers;
[net,TR]=train(net,entree,sortie,'UseParallel','yes');
%%%%%%%%  do and extract Mapping settings %%%%
[entree_map,entree_setMap] = mapminmax (entree);
[sortie_map,sortie_setMap] = mapminmax (sortie);
%%%  apply mapping setting + regression Modele test + mapping reverse %%%%%%%%%%%%%%%%
e=[1155 10 0.7 1.00017];
emap= mapminmax ('apply',e',entree_setMap);
b1 = net.b {1};
b2 = net.b {2};
IW = net.IW {1,1};
LW = net.LW {2,1};
B1=repmat(b1,1,N);
B2=repmat(b2,1,N);
a1=IW*emap+b1
h1=tansig(a1);
a2=LW*h1+b2;
h3_map=purelin(a2);
h= mapminmax('reverse',h3_map,sortie_setMap)
y=net(e')

, but it is a nother way to do it, and I think is the best:

https://fr.mathworks.com/matlabcentral/answers/311783-neural-network-how-can-i-get-the-correct-output-answer-without-using-the-function-sim-neural-net#answer_242993

此问题已关闭。

Obtaining an analytical function of regression and Understanding the reversing concept of the normalisation (of input data) automatically done by Matlab Neural Network.

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

回答（0 个）

另请参阅

标签

Community Treasure Hunt

Obtaining an analytical function of regression and Understanding the reversing concept of the normalisation (of input data) automatically done by Matlab Neural Network.

1 个评论 显示 -1更早的评论隐藏 -1更早的评论

回答（0 个）

另请参阅

标签

Community Treasure Hunt

1 个评论
显示 -1更早的评论隐藏 -1更早的评论