# Points from the image

blue$\_$points $=$ np$.$array$([[1,10],[1,9],[4,1],[6,0],[4,5],[5,9],[6,7],[9,7],[10,0]])$

red$\_$point $=$ np$.$array$([5,5])$

all

work must be done using Coding.

a$)(15$ points$)$ Nearest Neighbor Query $($Euclidean Distance$)$: Identify the nearest neighbor to the red querying point using the Euclidean distance.

b$)(15$ points$)$ Range Query $($Euclidean Distance$)$: List all blue points within a Euclidean distance of $3$ units

from the red querying point.

$1$

c$)(15$ points$)$ Range Query $($Euclidean Distance$)$: List all blue points within a Euclidean distance of $3$ units

from the red querying point.

d$)(15$ points$)$ Distance Comparison: Compare the Euclidean and Manhattan distances between the red

querying point $(5,5)$ and the blue point at $(9,6).$ Which distance is greater?

e$)(15$ points$)$ K$-$Nearest Neighbors $($Euclidean Distance$)$: Identify the $3$ nearest neighbors to the red querying point using the Euclidean distance.

f$)(15$ points$)$ K$-$Nearest Neighbors $($Manhattan Distance$)$: Identify the $3$ nearest neighbors to the red querying point using the Manhattan distance.

g$)(15$ points$)$ Cluster Identification $($Euclidean Distance$)$: Assuming a cluster radius of $2$ units, identify the

cluster of blue points that includes the red querying point using the Euclidean distance.