ABSTRACT
Ascending hierarchical clustering (AHC) constructs a hierarchy of individuals that is graphically represented by a hierarchical tree also named a dendrogram. Pruning this tree yields groups (clusters) of individuals. Hierarchical clustering requires to define a distance and an agglomerative criterion. Many distances are available (Manhattan, Euclidean, etc.) as well as several agglomeration methods (Ward, single, centroid, etc.).
