Algorithm 2: A standard agglomerative hierarchical clustering.

Data: n points $P_1,\dots ,P_n$

Result: A hierarchical clustering of $P_1,\dots ,P_n$

$C_i\leftarrow P_i,i=1,\dots ,n$;

$C\leftarrow \{C_1,\dots ,C_n\}$;

while $|C|>1$ do

$D_{ij}\leftarrow d_{BC}(C_i,C_j)$ for $C_i,C_j\in C$;

${\hat{C}}_i,{\hat{C}}_j\leftarrow \arg min{D}_{ij}$;

$C\leftarrow C+{\hat{C}}_i\cup {\hat{C}}_j$;

$C\leftarrow C-\{{\hat{C}}_i,{\hat{C}}_j\}$;

end