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).

`Prompt MAT,X`

dim MAT->D

D(1)->N

D(2)->D

{N,1}->V

For(I,1,N,1)

MAT(I)->M

0->S

For(J,1,D,1)

(M(J)-X(J))^{2}+S->S

End

âˆšS->V(I,1)

End

Disp V

To test it out, run KNN. Enter:

MAT? [[1,1][1,2]]

X? [1,1]

This tests points (1,1) and (1,2) against the point (1,1). You should get [[0][1]] as a result.