Methods of Hierarchical Clustering

Agglomerative hierarchical clustering has been the dominant approach to constructing embedded classification schemes. It is our aim to direct the reader's attention to practical algorithms and methods - both efficient (from the computational and storage points of view) and effective (from the application point of view). It is often helpful to distinguish between method, involving a compactness criterion and the target structure of a 2-way tree representing the partial order on subsets of the power set; as opposed to an implementation, which relates to the detail of the algorithm used. As with many other multivariate techniques, the objects to be classified have numerical measurements on a set of variables or attributes. Hence, the analysis is carried out on the rows of an array or matrix.