Consider a dataset with data points each having $3$ features, e$.$g$.,$ x$1=$ f$\backslash$Atlanta$"$; $\backslash$house$"$; $500$kg$,$

and x$2=$ f$\backslash$Houston$"$; $\backslash$house$"$; $300$kg$.$ Dene a proper similarity function d$($xi; xj$)$ for this kind of data,

and argue why it is a reasonable choice. $($Hint: The feature vector consists of categorial and real$-$valued

features; for categorical variables, it is better to convert them into one$-$hot$-$keying binary vectors and

use Hamming distance, and for real$-$valued features, you may use Euclidean distance, for instance. And

then you can combine the similarity measure in some way.$)$