41 lines
1.1 KiB
Matlab
41 lines
1.1 KiB
Matlab
% implements Bayes Testing, return the test error (p1: learned Bernoulli
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% parameters of the first class, p2: learned Bernoulli parameters of the
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% second class; pc1: best prior of the first class, pc2: best prior of the
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% second class
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function test_error = Bayes_Testing(test_data, p1, p2, pc1, pc2)
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% (1) TODO: classify the test set using the learned parameters p1, p2, pc1, pc2
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[test_row_size, column_size] = size(test_data); % dimension of test data
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X = test_data(1:test_row_size, 1:column_size-1); % test data
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y = test_data(:,column_size); % test labels
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c = 0;
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for i = 1:test_row_size
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x = X(i, :);
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correct_label = y(i);
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postc1 = prod(p1 .^ x .* (1 - p1) .^ (1 - x)) * pc1;
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postc2 = prod(p2 .^ x .* (1 - p2) .^ (1 - x)) * pc2;
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if postc1 > postc2
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lab = 1;
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else
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lab = 2;
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end
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if lab == correct_label
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c = c + 1;
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end
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end
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test_error = (test_row_size - c) / test_row_size;
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% (2) TODO: compute error rate and print it
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% (test_error = # of incorrectly classified / total number of test samples
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fprintf('Error rate on the test dataset is: \n\n');
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disp(test_error);
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end |