2023-10-12 23:51:06 +00:00
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% implements Classify, return the predicted class for each row (we'll call each row x) in data
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% by computing the posterior probability that x is in class 1 vs. class 2 then
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% these posterior probabilities are compared using the log odds.
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function [predictions] = Classify(data, m1, m2, S1, S2, pc1, pc2)
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2023-10-13 22:11:18 +00:00
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d = 8;
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2023-10-12 23:51:06 +00:00
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% TODO: calculate P(x|C) * P(C) for both classes
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2023-10-13 22:11:18 +00:00
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pxC1 = exp(-1/2*(data-m1)./S1*(data-m1)') / (power(2*pi,d/2) * sqrt(det(S1)));
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pxC2 = exp(-1/2*(data-m2)*(S2\(data-m2).'));
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g1 = pxC1 * pc1;
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g2 = pxC2 * pc2;
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2023-10-12 23:51:06 +00:00
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% TODO: calculate log odds, if > 0 then data(i) belongs to class c1, else, c2
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2023-10-13 22:11:18 +00:00
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for i = 1:length(data)
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data(i)
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end
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2023-10-12 23:51:06 +00:00
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% TODO: get predictions from log odds calculation
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end % Function end
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