Not really a KNN Classifier, as much as a mass, N-dimension euclidean distance calculator.
Input is a Matrix MAT of all the points to test against (row-based), and a Vector X the point to test against. Output is a Nx1 matrix V of all the distances between X and each row of the Matrix (in order).
Here’s a TI-85 program for the final that calculates the Mean Matrix, Covariances, Cv inverse, and the probability. I split it apart into two programs so that you can easily write down the answers and set your variables.
To calculate Mean, Covariance and Cv Inverse, enter the following into the program menu (I named mine GMEAN). The results are in variables called S and C (Cv Inverse is trivial to compute).