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Neural network training accuracy?
2 vues (au cours des 30 derniers jours)
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i want to make a plot of train accurancy how can i do that?
clc
clear all
close all
filename='FIFA7.xlsx';
A =xlsread(filename);
[m,n]=size(A);
T= A(:,1);
data= A(:,(2:end));
rows80=int32(floor(0.8 * m));
trainingset=A(1:rows80,:);
testset=A(rows80+1:end,:);
t=trainingset(1:rows80,1);
t_test=A(rows80+1:end,1);
% k=10;
%
% cvFolds = crossvalind('Kfold', t, k);
% for i = 1:k
% testIdx = (cvFolds == i);
% trainIdx = ~testIdx ;
% trInd=find(trainIdx)
% tstInd=find(testIdx)
% net.trainFcn = 'trainbr'
% net.trainParam.epochs = 100;
% net.divideFcn = 'divideind';
% net.divideParam.trainInd=trInd
% net.divideParam.testInd=tstInd
% Choose a Performance Function
% net.performFcn = 'mse'; % Mean squared error
% end
k=10
cvFolds = crossvalind('kfold',t,k);
for i =1:k
testIdx = (cvFolds == i);
trainIdx = ~testIdx ;
trInd=find(trainIdx)
tstInd=find(testIdx)
end
net= newff(trainingset',t');
y=sim(net,trainingset');
%net.trainParam.epoch=20;
net= train(net,trainingset',t');
y=sim(net,trainingset');
y_test=sim(net,testset');
p=0;
y1=hardlim(y');
y2= hardlims(y_test);
for(i=1:size(t,1))
if(t(i,:)==y1(i,:))
p=p+1;
end
end
trainerror =100*p/size(trainingset,1);
e=0;
y2=hardlim(y_test');
for(j=1:size(t_test,1))
if(t_test(j,:)==y2(j,:))
e=e+1;
end
end
testerror=100*e/size(t_test,1)
plot( testIdx ,'.');
1 commentaire
Greg Heath
le 5 Déc 2018
Modifié(e) : Greg Heath
le 5 Déc 2018
2. I think the best measures of regression accuracy are
NMSE = mse( t - y ) / mse( t - mean( t ))
and
RSQUARE = 1 - NMSE (See Wikipedia)
3. Then, the goodness of fit in [0 1 ] is IMMEDIATELY recognized !
Greg
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