Dear all
I can change the output (D)
clear all, clc
rng(3);
X = zeros(5, 5, 5);
X(:, :, 1) = [ 0 1 1 0 0;
0 0 1 0 0;
0 0 1 0 0;
0 0 1 0 0;
0 1 1 1 0
];
X(:, :, 2) = [ 1 1 1 1 0;
0 0 0 0 1;
0 1 1 1 0;
1 0 0 0 0;
1 1 1 1 1
];
X(:, :, 3) = [ 1 1 1 1 0;
0 0 0 0 1;
0 1 1 1 0;
0 0 0 0 1;
1 1 1 1 0
];
X(:, :, 4) = [ 0 0 0 1 0;
0 0 1 1 0;
0 1 0 1 0;
1 1 1 1 1;
0 0 0 1 0
];
X(:, :, 5) = [ 1 1 1 1 1;
1 0 0 0 0;
1 1 1 1 0;
0 0 0 0 1;
1 1 1 1 0
];
D = [ 1 0 0 0 0; % what to write D as [1 2 3 4 5; 0 1 2 3 4; etc]
0 1 0 0 0;
0 0 1 0 0;
0 0 0 1 0;
0 0 0 0 1
];
W1 = 2*rand(50, 25) - 1;
W2 = 2*rand( 5, 50) - 1;
for epoch = 1:10000 % train
[W1 W2] = MultiClass(W1, W2, X, D);
end
N = 5; % inference
for k = 1:N
x = reshape(X(:, :, k), 25, 1);
v1 = W1*x;
y1 = Sigmoid(v1);
v = W2*y1;
y = Softmax(v)
end
When i rewrite the D it show error of NaN....
FUNCTIONS
function [W1, W2] = MultiClass(W1, W2, X, D)
alpha = 0.9;
N = 5;
for k = 1:N
x = reshape(X(:, :, k), 25, 1);
d = D(k, :)';
v1 = W1*x;
y1 = Sigmoid(v1);
v = W2*y1;
y = Softmax(v);
e = d - y;
delta = e;
e1 = W2'*delta;
delta1 = y1.*(1-y1).*e1;
dW1 = alpha*delta1*x';
W1 = W1 + dW1;
dW2 = alpha*delta*y1';
W2 = W2 + dW2;
end
end
function y = Sigmoid(x)
y = 1 ./ (1 + exp(-x));
end
function y = Softmax(x)
ex = exp(x);
y = ex / sum(ex);
end

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Adam Danz
Adam Danz 2019년 12월 18일
편집: Adam Danz 2019년 12월 18일
I edited your question to format the code. In the future, please format your code in all questions, comments, and answers (I see you've got some experience here so that should be clear by now).
"When i rewrite the D it show error of NaN.... "
I run your code without error.

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2019년 12월 18일

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2019년 12월 18일

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