How can i evaluate my network performance as i have trained my model?

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Machine Learning Enthusiast
编辑： Machine Learning Enthusiast 2017-2-20
I have trained my model with 100% accuracy,but i want to evaluate my trained work from test data set or unseen data.what should i add in my code for testing purpose? i-e to test validation data and test data
p = u; %inputs
t = f; %targets
[pn,ps] = mapminmax(p);
[tn,ts] = mapminmax(t);
%net = newff(p,t,10,10{},'trainlm');
net=newff(minmax(pn),[30,25,16],{'tansig','tansig','purelin'},'trainscg');
%net = init(net);
% net.IW{1,1}=wts0;
% net.b{1}=bias0;
net.trainParam.show =2;
net.trainParam.epochs =5000;
net.trainParam.goal =1e-7;
%net.trainParam.mc=0.95;
net.trainParam.lr=0.2;
[net,tr] = train(net,pn,tn);
ANN = sim(net,pn);
output1= mapminmax('reverse',ANN,ts);
wts1=net.IW{1,1};
bias1=net.b{1};

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Walter Roberson
Walter Roberson 2017-2-18
  7 个评论
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Walter Roberson
Walter Roberson 2017-2-18
The code for that example does not create a network named "net". Are you trying to apply that to deepnet just before
% Train the deep network on the wine data.
?
Machine Learning Enthusiast
Machine Learning Enthusiast 2017-2-20
编辑：Machine Learning Enthusiast 2017-2-20
yes....i am not sure about the syntax "deepnet" or only "net".i want to divide my data into train,validation and test as given below and at the end i am trying to get confusion matrix with validation and test set as shown in attached figure.
% Setup Division of Data for Training, Validation, Testing
deepnet.divideParam.trainRatio = 80/100;
deepnet.divideParam.valRatio = 10/100;
deepnet.divideParam.testRatio = 10/100;

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