As defined by P. H. A. Sneath and R. R. Sokal, the grouping by numerical methods of taxonomic units based on their character states. According to G. G. Simpson, taxonomy is the theoretical study of classification, including its bases, principles, procedures, and rules. The application of numerical methods to taxonomy, dating back to the rise of biometrics in the late nineteenth century, has received a great deal of attention with the development of the computer and computer technology. Numerical taxonomy provides methods that are objective, explicit, and repeatable, and is based on the ideas first put forward by M. Adanson in 1963. These ideas, or principles, are that the ideal taxonomy is composed of information-rich taxa (“taxon,” plural “taxa,” is the abbreviation for taxonomic group of any nature or rank as suggested by H. Lam) based on as many features as possible, that a priori every character is of equal weight, that overall similarity between any two entities is a function of the similarity of the many characters on which the comparison is based, and that taxa are constructed on the basis of diverse character correlations in the groups studied.