Introduction

Abstract

Classifying objects according to their likeness seems to have been, for all time, a step in the human process of acquiring knowledge. We could possibly find the beginning of this process as early as infancy, if we admit that the brain of a young child learns to distinguish categories of objects or persons (distinguishing one animal from another, his parents from strangers,…), or of situations (what is allowed from what is not) proceeding by analogies. Historically the scientific process, even when it is purely descriptive, works in the same way. We dominate well a domain when all its notions are classified and categorised. Such classifications show some relationships from which the exploration yields, in a second stage, improvements in the knowledge of the domain. Even far back in time, we find texts and authors who have shown organisation and clustering particularly in descriptions in the areas of botany or geology (Aristotle). Closer to us, the scientists of the “siècle des lumières” and their heirs introduced some famous classifications (A.L. de Jussieu, G. Cuvier, G. L. Buffon, C. von Linneaus,…). In the same way, we can find, outside natural science, various works in classification in the exact sciences (D.I. Mendeleïev,…), in astronomy or in linguistics (see Marcotorchino (1991) for an interesting historical presentation). The criteria of classification used are generally empirical ones: mammals are separated from nonmammals, vertebrates from non vertebrates,‖ In a modern context, this is equivalent to deriving a hierarchical clustering of objects (we use this generic name for individuals, or statistical units, Operational Taxonomic Units (OTU),…) using some variables which are introduced one after another in a given order.

In Van Cutsem, B. (Ed.), (1994) Classification and Dissimilarity Analysis, Lecture Notes in Statistics, Springer-Verlag, New York.