Training Dataset:

$\backslash$table$[[,x,y,$Class Label$],[$Point $1,0,3,$Positive$],[$Point $2,1,3,$Positive$],[$Point $3,2,2,$Positive$],[$Point $4,1,1,$Positive$],[$Point $5,3,1,$Negative$],[$Point $6,3,2,$Negative$],[$Point $7,4,1,$Negative$],[$Point $8,4,2,$Negative$]]$

Manhattan Distance $($grid distance$)$ between two points is the sum of the absolute difference between the coordinates:

Distance $(p,q)=L_1(p,q)={\displaystyle \underset{i=1}{\overset{d}{}}}|p_i-q_i|$

Consider the testing point $(2,1),$ using $KNN$ classifier with $k=3,$ and the manhattan distance as the distance measure, what is the predicted class label of the testing point.

Distances $=$

$\backslash$table$[[,$Point$1,$Point$2,$Point$3,$Point$4,$Point$5,$Point$6,$Point$7,$Point$8],[$Distance$,,,,,,,,],[$Label$,,,,,,,,]]$

What is the predicted class label for the same testing point $(2,1)$ when using $k=5$