Consider a dataset with data points each having $3$ features, e$.$g$.,$ x$1=\{"$Atlanta$",$ "house", $500$k$\},$ and x$2=\{"$Houston$",$"house",$300$k$\}.$ Define 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.$)$