How to solve

Consider a $2-$D training dataset with three samples from class $,$ located at $(0\mathrm{.}5,0\mathrm{.}5),(1\mathrm{.}5,1\mathrm{.}5),$ and $(2\mathrm{.}5,0\mathrm{.}5),$ and three samples from class $o.,$ located at $(0\mathrm{.}5,1\mathrm{.}5),(1\mathrm{.}5,0\mathrm{.}5),$ and $(2\mathrm{.}5,1\mathrm{.}5),$ as shown in Figure $1.$ If each of the following classifiers, based on the Euclidean distance measure, is used to performance the classification, shade the regions $($within $0x3$ and $0y2)$ where a test sample located in them would be classified as class $.$

$($a$)1-$Nearest Neighbor Classifier $(1-$NN$)$

$($b$)3-$Nearest Neighbor Classifier $(3-$NN$)$

$($c$)5-$Nearest Neighbor Classifier $(5-$NN$)$

$[2$ Marks$]$