Q$3.$ Consider the problem of finding the $K$ nearest neighbors of a data object. Use the below given object dataset for answering the questions.

$8+2=10$

Algorithm: Finding the $K$ nearest neighbors

For $i=1$ to number of data objects

Find the proximity of the $i^t$ object to all other objects

Sort these proximities in decreasing order

$($Keep track of which object is associated with each proximity value$)$

Return the first $K$ objects of the sorted list

End for

$\backslash$table$[[$Data object,Name,Gender,Salary,Age$],[$Obj$1,$AFD,Male,High,Old$],[$Obj$2,$SRE,Male,Low,Middle$],[$Obj$3,$SDF$,$Female,High,Young$],[$Obj$4,$AQW,Male,Low,Middle$],[$Obj$5,$ASW,Female,High,Young$]]$

a$)$ Which are the $3$ nearest object of Obj$1$ using

I. Euclidian distance measure

II$.$ Cosine similarity measure

b$)$ Do you see any challenges with respect to this algorithm which are associated with data quality that might impact the outcome? How you will fix it$?$