36 lines
1,001 B
Matlab
36 lines
1,001 B
Matlab
function [] = Problem1(training_file, test_file)
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% Variables
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part = {'1' '2' '3'};
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% load data
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training_data = load(training_file);
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test_data = load(test_file);
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% Remove label from data
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training_labels = training_data(:, end);
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training_data(:, end) = [];
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test_labels = test_data(:, end);
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test_data(:, end) = [];
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% Learn prior probabilities
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pc1 = sum(training_labels==1)/size(training_labels,1);
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pc2 = 1-pc1;
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for i = 1:length(part)
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fprintf('Model %s: ', part{i});
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% Training for Multivariate Gaussian
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[m1, m2, S1, S2] = Param_Est(training_data, training_labels, part(i));
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[predictions] = Classify(training_data, m1, m2, S1, S2, pc1, pc2);
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fprintf('(train err = ');
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Error_Rate(predictions, training_labels);
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fprintf('), ');
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% Testing for Multivariate Gaussian
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[predictions] = Classify(test_data, m1, m2, S1, S2, pc1, pc2);
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fprintf('(test error = ');
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Error_Rate(predictions, test_labels);
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fprintf(')\n');
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end
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