34 lines
No EOL
786 B
Matlab
34 lines
No EOL
786 B
Matlab
% CSCI 5521 Introduction to Machine Learning
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% Rui Kuang
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% Run perceptron on random data points in two classes
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n = 20; %set the number of data points
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mydata = rand(n,2);
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shiftidx = abs(mydata(:,1)-mydata(:,2))>0.05;
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mydata = mydata(shiftidx,:);
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myclasses = mydata(:,1)>mydata(:,2); % labels
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n = size(mydata,1);
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X = [mydata ones(1,n)']'; Y=myclasses;
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Y = Y * 2 -1;
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% init weigth vector
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w = [mean(mydata) 0]';
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for i = 1:1
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w=rand(1,3)';
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w(3,1)=0;%go through the origin for visualization
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% call perceptron
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wtag=perceptron(X,Y,w,10);
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end
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% call perceptron
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% wtag=perceptron(X,Y,w);
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% predict
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ytag=wtag'*X;
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% plot prediction over origianl data
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%plot(X(1,ytag<0),X(2,ytag<0),'bo')
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%plot(X(1,ytag>0),X(2,ytag>0),'ro')
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%legend('class -1','class +1','pred -1','pred +1') |