Q$4$ k$-$Nearest Neighborhood

$36$ Points

Grading comment:

Consider a binary classification problem with two real valued features x$1$x$1$ and x$2$x$2.$ Figures $1$ and $2$ illustrate two different training sets S$1$S$1$ and S$2$S$2.$ White circles indicate the positively$-$labeled examples, whereas black squares indicate the negatively$-$labeled examples. To classify a new instance point, we will use $($unweighted$)$ kk$-$Nearest Neighbors with Euclidean distance and different kk values. Thus the label for a new point will be predicted by the majority class $($i$.$e$.,$ positive or negative$)$ among the k closest examples around the query point.