Parameters of various hierarchical clustering methods.

β, ɣ: corrections based on the triangle ijk; Dissimilarity [E2: Euclidean distance; E2′: half of the squared Euclidean distance]; Monotony [monotonically increasing lengths (We note that this is not true in the centroid and median methods. The value of a monotonic increase depends on the particular situation.); T: true; F: false;]; Metric [expansion & reduction: renewal of ongoing clustering by increasing or reducing the distance between data points].