필터 지우기
필터 지우기

Neural network training accuracy?

조회 수: 1 (최근 30일)
Narges Sedre
Narges Sedre 2018년 12월 4일
편집: Greg Heath 2018년 12월 5일
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 ,'.');
  댓글 수: 1
Greg Heath
Greg Heath 2018년 12월 5일
편집: Greg Heath 2018년 12월 5일
  1. Does it really make sense to you to post tens of lines of code without a sample of relevant data ???
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

댓글을 달려면 로그인하십시오.

답변 (0개)

카테고리

Help CenterFile Exchange에서 Deep Learning Toolbox에 대해 자세히 알아보기

Community Treasure Hunt

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

Start Hunting!

Translated by