% implements Classify, return the predicted class for each row (we'll call each row x) in data
% by computing the posterior probability that x is in class 1 vs. class 2 then 
% these posterior probabilities are compared using the log odds.
function [predictions] = Classify(data, m1, m2, S1, S2, pc1, pc2)

  % calculate P(x|C) * P(C) for both classes
    
  pxC1 = mvnpdf(data, m1, S1);
  pxC2 = mvnpdf(data, m2, S2);

  g1 = log(pxC1 * pc1);
  g2 = log(pxC2 * pc2);

  % TODO: calculate log odds, if > 0 then data(i) belongs to class c1, else, c2
  log_odds = g1 - g2;
  % for i = 1:length(data)
  %     if g1 > g2
  %         predictions(i) = 1;
  %     else
  %         predictions(i) = 2;
  %     end
  % end
  
  % TODO: get predictions from log odds calculation
  [num_rows, ~] = size(data);
  predictions = zeros(num_rows,1);
  for i = 1:num_rows
      predictions(i) = log_odds(i) > 0;
  end
  
end % Function end