33 lines
698 B
Mathematica
33 lines
698 B
Mathematica
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% CSCI 5521 Introduction to Machine Learning
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% Rui Kuang
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% Demonstration of Classification by 1-D Gaussians
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%mean and standard deviation of class blue
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mu1 = -2;sd1 = 2;
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%mean and standard deviation of class red
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mu2 = 2;sd2 = 4;
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%generate x-axis
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sd = max(sd1,sd2);
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ix = -6*sd-1:1e-1:6*sd+1; %covers more than 99% of the curve
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iy1 = pdf('normal', ix, mu1, sd1);
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iy2 = pdf('normal', ix, mu2, sd2);
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subplot(1,2,1);
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plot(ix,iy1,'b'); hold on;
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plot(ix,iy2,'r');
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title('PDF P(X)');
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%prior
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p1=0.8;
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p2=1-p1;
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%calculate the posteriors
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iy1_n = p1*iy1 ./ (p1*iy1+p2*iy2);
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iy2_n = p2*iy2 ./ (p1*iy1+p2*iy2);
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subplot(1,2,2);
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plot(ix,iy1_n,'b'); hold on;
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plot(ix,iy2_n,'r');
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title('Posteriors P(C | x)');
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