February 2019
Intermediate to advanced
386 pages
9h 54m
English
An important feature of agglomerative hierarchical clustering is the possibility to include connectivity constraints to force the merging of specific samples. This kind of prior knowledge is very common in contexts where there are strong relationships between neighbors or when we know that some samples must belong to the same cluster because of their intrinsic properties. To achieve this goal, we need to use a connectivity matrix, A ∈ {0, 1}n × n:

In general, A is the adjacency matrix induced by a graph of the dataset; however, the only important requirement is the absence of isolated samples (without connections), ...