% 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)

  d = 8;

  % TODO: calculate P(x|C) * P(C) for both classes
    
  pxC1 = exp(-1/2*(data-m1)./S1*(data-m1)') / (power(2*pi,d/2) * sqrt(det(S1)));
  pxC2 = exp(-1/2*(data-m2)*(S2\(data-m2).'));

  g1 = pxC1 * pc1;
  g2 = pxC2 * pc2;

  % TODO: calculate log odds, if > 0 then data(i) belongs to class c1, else, c2
  for i = 1:length(data)
      data(i)
  end
  
  % TODO: get predictions from log odds calculation
  
end % Function end