ffaltacross.m

cross validation of training data

fid = fopen('altrainset.txt');
A = fscanf(fid,'%f %f %f %f',[4 inf]); % It has four rows now.
A = A';
fclose(fid);

b = [A(:,1:3)];
 c = [A(:,4:4)];
 
 d=c';
 
p = b';
t = d;

fid1 = fopen('alvalidationset.txt');
AV = fscanf(fid1,'%f %f %f %f',[4 inf]); % It has four rows now.
AV = AV';
fclose(fid1)

bv = [AV(:,1:3)];
 cv = [AV(:,4:4)];
 
 dv=cv' ;
 
pv = bv';
tv = dv;
val.P=pv;
val.T=tv;
net=newff(minmax(p),[5,10,1],{'tansig','tansig','purelin'},'traingdx');
net.trainParam.show = 5;
net.trainParam.epochs = 300;
%net.trainParam.goal = 1e-5;
net = init(net);
for i=1:5:50
    net = init(net);
 %   net.trainParam.epochs = 100;
%net = init(net);
[net,tr]=train(net,p,t,[],[],val);
plotperf(tr)
iterations=i
X = getx(net);
X=X';
end
%net=newff(minmax(p),[5,10,1],{'tansig','tansig','purelin'},'traingdx');
%net=init(net);

%net.trainParam.show = 5;
%net.trainParam.epochs = 1;
%i=net.trainParam.epochs;
%net.trainParam.goal = 1e-5;
%for i=1:100:1000
 %   net.trainParam.epochs = 100;
%[net,tr]=train(net,p,t);
%[net,tr]=train(net,pv,tv);
%iterations=i
%X = getx(net);
%X=X'
%end
a = sim(net,p);
av=sim(net,pv);
InputSource=net.numInputs;
NumLayers=net.numLayers ;
NumInputs =net.inputs{1}.size;
layer1Size=net.layers{1}.size;
layer2Size =net.layers{2}.size;
layer3Size =net.layers{3}.size;

b1 = net.b{1};
b2 = net.b{2};
b3 = net.b{3};
iw1 = net.iw{1,1};
    lw21 = net.lw{2,1};
    lw32 = net.lw{3,2};

X = getx(net);
X=X';

wts1=net.LW{1,1};
lengthWgtlayr1=length(wts1);
wts2=net.LW{2,1};
lengthWgtlayr2=length(wts2);
wts3=net.LW{3,1};
lengthWgtlayr3=length(wts3);

lengthWeights=length(X);


fid2 = fopen('ALCROSS5cgf.txt','w');
fprintf(fid2,'%f   \n', X);
%fprintf(fid1,'\n %f %f \t %f %f \t  %f  %f \t ', wts1, lengthWgtlayr1,  wts2, lengthWgtlayr2, wts3, lengthWgtlayr3 );
fclose(fid2);

z= [0.7143; 0.0; 1.0;]; 
x= z'
a = sim(net,z);
ap = sim(net,p);
ap=ap';
Y=horzcat(b,ap,c);
fid2 = fopen('ALCROSS5cgfOut.txt','w');
fprintf(fid2,'%f   \n',ap);
Y=Y';
fprintf(fid2,'\n %f  %f  %f  %f  %f   \n',Y);
fclose(fid2);

%net.inputWeights