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POcreating a train perceptron in MATLAB for gender clasiffication
 

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  1. POcreating a train perceptron in MATLAB for gender clasiffication
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    <p>I am coding a perceptron to learn to categorize gender in pictures of faces. I am very very new to MATLAB, so I need a lot of help. I have a few questions:</p> <ol> <li><p>I am trying to code for a function:</p> <pre><code>function [y] = testset(x,w) %y = sign(sigma(x*w-threshold)) </code></pre> <p>where y is the predicted results, x is the training/testing set put in as a very large matrix, and w is weight on the equation. The part after the <code>%</code> is what I am trying to write, but I do not know how to write this in MATLAB code. Any ideas out there?</p></li> <li><p>I am trying to code a second function: </p> <pre><code>function [err] = testerror(x,w,y) %err = sigma(max(0,-w*x*y)) </code></pre> <p>w, x, and y have the same values as stated above, and err is my function of error, which I am trying to minimize through the steps of the perceptron.</p></li> <li><p>I am trying to create a step in my perceptron to lower the percent of error by using gradient descent on my original equation. Does anyone know how I can increment w using gradient descent in order to minimize the error function using an if then statement?</p></li> </ol> <p>I can put up the code I have up till now if that would help you answer these questions.</p> <p>Thank you!</p> <p>edit-------------------------- </p> <p>OK, so I am still working on the code for this, and would like to put it up when I have something more complete. My biggest question right now is: </p> <p>I have the following function: </p> <pre><code>function [y] = testset(x,w) y = sign(sum(x*w-threshold)) </code></pre> <p>Now I know that I am supposed to put a threshold in, but cannot figure out what I am supposed to put in as the threshold! any ideas out there?</p> <p>edit----------------------------<br> this is what I have so far. Changes still need to be made to it, but I would appreciate input, especially regarding structure, and advice for making the changes that need to be made!</p> <pre><code>function [y] = Perceptron_Aviva(X,w) y = sign(sum(X*w-1)); end function [err] = testerror(X,w,y) err = sum(max(0,-w*X*y)); end %function [w] = perceptron(X,Y,w_init) %w = w_init; %end %------------------------------ % input samples X = X_train; % output class [-1,+1]; Y = y_train; % init weigth vector w_init = zeros(size(X,1)); w = w_init; %--------------------------------------------- loopcounter = 0 while abs(err) &gt; 0.1 &amp;&amp; loopcounter &lt; 100 for j=1:size(X,1) approx_y(j) = Perceptron_Aviva(X(j),w(j)) err = testerror(X(j),w(j),approx_y(j)) if err &gt; 0 %wrong (structure is correct, test is wrong) w(j) = w(j) - 0.1 %wrong elseif err &lt; 0 %wrong w(j) = w(j) + 0.1 %wrong end % ----------- % if sign(w'*X(:,j)) ~= Y(j) %wrong decision? % w = w + X(:,j) * Y(j); %then add (or subtract) this point to w end </code></pre>
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    1. COThe Matlab documentation itself if fairly thorough and gives background material,small examples, and references. Pull some papers specific to your field and see what methodologies they used.
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    2. COWhat have you tried and what isn't working? Do you have a specific question?
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    3. COCan you put all the code you have.
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