Suppose we have the following 2-D data set: Given a new data point, $d = (1.4, 1.6)$
\begin{tabular}{|c|c|c|}
\hline
& x & y \\
\hline
$d_1$ & 1.5 & 1.7 \\
$d_2$ & 2 & 1.9 \\
$d_3$ & 1.6 & 1.8 \\
$d_4$ & 1.2 & 1.5 \\
$d_5$ & 1.5 & 1.0 \\
\hline
\end{tabular}
as a query, rank the database points based on similarity (from the most similar to
the least similar) with the query using Euclidean distance, Manhattan distance,
supremum distance, and cosine similarity.
