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classifyMusic.m
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classifyMusic.m
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%% Initialization
clear ; close all; clc
%% Load Data
data = load('dataSet');
X = data(:, [1, 2]); y = data(:, 3);
fprintf(['Plotting data with + indicating (y = 1) examples and o ' ...
'indicating (y = 0) examples.\n']);
plotData(X, y);
hold on;
% Labels and Legend
xlabel('Variance')
ylabel('Mean')
% Specified in plot order
legend('Classical', 'Metal')
hold off;
fprintf('\nProgram paused. Press enter to continue.\n');
pause;
[m, n] = size(X);
X = [ones(m, 1) X];
initial_theta = zeros(n + 1, 1);
[cost, grad] = costFunction(initial_theta, X, y);
fprintf('Cost at initial theta (zeros): %f\n', cost);
fprintf('Gradient at initial theta (zeros): \n');
fprintf(' %f \n', grad);
fprintf('\nProgram paused. Press enter to continue.\n');
pause;
options = optimset('GradObj', 'on', 'MaxIter', 400);
[theta, cost] = ...
fminunc(@(t)(costFunction(t, X, y)), initial_theta, options);
fprintf('Cost at theta found by fminunc: %f\n', cost);
fprintf('theta: \n');
fprintf(' %f \n', theta);
plotDecisionBoundary(theta, X, y);
hold on;
xlabel('Variance')
ylabel('Mean')
legend('Classical', 'Metal')
hold off;
fprintf('\nProgram paused. Press enter to continue.\n');
pause;
prob = sigmoid([1 -20.2274813694 9.10379315836] * theta);
fprintf(['For a music the prob is %f\n\n'], prob);
fprintf('\nProgram paused. Press enter to continue.\n');
pause;