MATLAB: Is the mean square value changing to an another value for a different training function

Question

clc; clear all;close all;

seed = 2;

rand('seed',0);

co=1; % Testing takes pleace for co number of runs and average is returned

meanTrain=0; %mean performacne of training data

meanTest=0; %mean performacne of testing data

tn_data = xlsread('D:\PROJECT\back prop\train_data.xlsx');

s1 = tn_data;

tn_test = xlsread('D:\PROJECT\back prop\train_test.xlsx');

s2 = tn_test;

tt_data = xlsread('D:\PROJECT\back prop\test_data.xlsx');

s3 = tt_data;

tt_test = xlsread('D:\PROJECT\back prop\test_test.xlsx');

s4 = tt_test;

in=s(:,3:3); %in contains all inputs

ou=s(:,2:2); %ou contains all outputs

for i=1:co

    trainInput=[];
    trainOutput=[];
    testInput=[];
    testOutput=[];
    trainInput = s1;
    trainOutput = s2;
    testInput = s3;
    testOutput = s4;
    inn = [trainInput' testInput'];
    in = inn(:)
    % network initialization
    net=newff(minmax(in'),[20,1],{'tansig','purelin'},'traingdm_new');
    net.trainParam.show = 50;
    net.trainParam.lr = 0.01;
    net.trainParam.mc = 0.1;
    net.trainParam.epochs = 5000;
    net.trainParam.goal = 2e-2;
    % training
    [net,tr]=train(net,trainInput',trainOutput');
    % testing on training data
    a = sim(net,trainInput');
    a=a';
    corr=0;
    for j=1:size(trainInput,1)
        if a(j)< 0.49 ans=0; else ans=1; end
        if trainOutput(j)==ans corr=corr+1; 
        fprintf('\n the %d th image is correctly classified',j);
        end
    end
    corr; 
    corr/size(trainInput,1)*100; % percent train accuracy
    meanTrain=meanTrain+corr;
    % testing on testing data
    a = sim(net,testInput');
    a=a';
    corr=0;
    for j=1:size(testInput,1)
        if a(j)< 0.49 ans=0; else ans=1; end
        if testOutput(j)==ans corr=corr+1; 
            q(j) = corr;
        fprintf('\n the %d th image is correctly classified',j);
        end
    end
    corr;
    meanTest=meanTest+corr;
    corr/size(testInput,1)*100; % percent test accuracy

end

s=size(trainInput,1);

%'Mean Train Recognized'

ttt =meanTrain;

ttit=meanTrain/co;

'Mean Train Recognition Accuracy'

result1 = (meanTrain/co)/s*100 % mean percent train accuracy

s=size(testInput,1);

%'Mean Test Recognized'

ttet = meanTest;

tet = meanTest/co;

'Mean Test Recognition Accuracy'

result2 = (meanTest/co)/s*100 % mean percent test accuracy

e = testOutput – a;

perf1 = mse(e)

%%%%%%%%%%%%%%%%%%%%%%%%%%%% Code ends %%%%%%%%%%%%%%%%%%%%

The Test Accuracy that I get is 93.33 % and the mean square error is 0.1031

I have used the training function "traingdm".

If I use the training function "trainbr" and its corresponding training parameters, the classification percentage is 93.33%

But the mean square error changes to some other value. Why is this happening ????

Answer 1

 help trainbr
 Note that
 "trainbr ... minimizes a combination of squared errors and weights"

Hope this helps.

Greg