Determining Ties in Mode of Matrix

Let's say I have a matrix

A = [1 2 3 4
     2 3 4 1
     1 2 3 4
     2 5 5 1]

and I take the mode of A

[M, F, C] = mode(A)

How would I go about selecting only the values in M where there was a tie and then replacing only those values? I've read that

cellfun('length',C) > 1

would tell you what values in M would have a tie, but I'm not sure how to incorporate that into replacing only the certain values where ties occurred.

Answer 1

[Image Analyst]

This will do it:

A = [1 2 3 4
     2 3 4 1
     1 2 3 4
     2 5 5 1]
 % Find the mode of A.  It will be 1.
 modeOfA = mode(A(:))
 % Find elements where the mode is
 modeLocations = A == modeOfA
 % Replace mode with 99
 A(modeLocations) = 99

If you want it done all in one cryptic, harder to follow, but compact single line of code, you can do this:

A(A==mode(A(:))) = 99

[Bradley Flynn]

I probably should have specified that mode of A is not the mode of the matrix but rather the mode of each column vector.

[Image Analyst]

Tell us what you would like to see as an output. What do you want to replace the mode value with?

If it's 99, then try this code:

A = [1 2 3 4
  2 3 4 1
  1 2 3 4
  2 5 5 1]
for col = 1 : size(A, 2)
  thisColumn = A(:, col);
  % Find the mode of A.  It will be 1.
  modeOfA = mode(thisColumn)
  % Find elements where the mode is
  modeLocations = thisColumn == modeOfA
  % Replace mode with 99
  A(modeLocations, col) = 99
end

[Bradley Flynn]

I'm trying to code my own knn and I want a good way to resolve ties without a for-loop. I did some thinking and came up with this if you're interested:

    [preds, F, C]= mode(class);   
    if ~(all(cellfun('length',C)==1))
        keep = cellfun('length',C)==1;
        remove = cellfun('length',C) > 1;
        preds = preds.*keep;
        updated = remove.*knnclassifier(xTr,yTr,xTe,k-1);
        preds = preds + updated;
    end