how to classify two class using neural network

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tamanna 2013-4-16

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https://ww2.mathworks.cn/matlabcentral/answers/72208-how-to-classify-two-class-using-neural-network

采纳的回答： Greg Heath

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Answer 1

Greg Heath 2013-4-16

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此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/72208-how-to-classify-two-class-using-neural-network#answer_82384

patternnet

help patternnet

doc patternnet

Hope this helps.

Greg

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tamanna 2013-4-30

在 MATLAB Online 中打开

sir..this is the coding i got from somewhere for probabilistic neural network. X = [7.02 1;50.13 5;90.1 9;86.08 9;62 4;59.9 15;35.6 20;35.5 60;70.89 48;40.3 80]';

Tc = [1 2 3 4 5 6 7 8 9 10];

plot(X(1,:),X(2,:),'.','markersize',20)

 for i=1:10
text(X(1,i)+0.1,X(2,i),sprintf('class %g',Tc(i))),
 end
% axis([0 200 0 200])
 title('Ten vectors and their classes.')
xlabel('X(1,:)')
ylabel('X(2,:)')

%.......................................

T = ind2vec(Tc);

spread = 1;

net = newpnn(X,Tc,spread); ........................................%

% Y = sim(net,X,Tc);

% Y = net(X);

 Y= X';
Yc = vec2ind(Y);
figure;
plot(X(1,:),X(2,:),'.','markersize',30)
% axis([0 200 0 200])
for i=1:10,text(X(1,i)+0.1,X(2,i),sprintf('class %g',Yc(i))),
end
title('Testing the network.')
xlabel('X(1,:)')
ylabel('X(2,:)')

%......................................%

x = [20; 10.5];

y=x';

% y = net(x);

ac = vec2ind(y);

hold on

plot(x(1),x(2),'.','markersize',30,'color',[1 0 0])

text(x(1)+0.1,x(2),sprintf('class %g',ac))

hold off

title('Classifying y new vector.')

xlabel('X(1,:) and x(1)')

ylabel('X(2,:) and x(2)')

may you tell me what the flow of the program

tamanna 2013-4-30

在 MATLAB Online 中打开

sir..this is the coding i got from somewhere for probabilistic neural network. X = [7.02 1;50.13 5;90.1 9;86.08 9;62 4;59.9 15;35.6 20;35.5 60;70.89 48;40.3 80]';

Tc = [1 2 3 4 5 6 7 8 9 10];

plot(X(1,:),X(2,:),'.','markersize',20)

 for i=1:10
text(X(1,i)+0.1,X(2,i),sprintf('class %g',Tc(i))),
 end
% axis([0 200 0 200])
 title('Ten vectors and their classes.')
xlabel('X(1,:)')
ylabel('X(2,:)')

%.......................................

T = ind2vec(Tc);

spread = 1;

net = newpnn(X,Tc,spread); ........................................%

% Y = sim(net,X,Tc);

% Y = net(X);

 Y= X';
Yc = vec2ind(Y);
figure;
plot(X(1,:),X(2,:),'.','markersize',30)
% axis([0 200 0 200])
for i=1:10,text(X(1,i)+0.1,X(2,i),sprintf('class %g',Yc(i))),
end
title('Testing the network.')
xlabel('X(1,:)')
ylabel('X(2,:)')

%......................................%

x = [20; 10.5];

y=x';

% y = net(x);

ac = vec2ind(y);

hold on

plot(x(1),x(2),'.','markersize',30,'color',[1 0 0])

text(x(1)+0.1,x(2),sprintf('class %g',ac))

hold off

title('Classifying y new vector.')

xlabel('X(1,:) and x(1)')

ylabel('X(2,:) and x(2)')

may you tell me what the flow of the program

Greg Heath 2013-5-1

I have a better idea:

1. Run the program

2. Run again with semicolons removed

3. Study the results

4. If you have any questions, repost with comments before every line you understand and a line of question marks before every line you do not understand.

Greg

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how to classify two class using neural network

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