title: A maximal predictive classification of Klebsielleae and of the yeasts.
abstract: The concepts of the numerical method of maximal predictive classification are illustrated with classifications of 13 species of enterobacteria and of 434 species of yeast. The method seeks to classify into a specified number of classes (k) such that more correct statements can be made about the constituent members than with any other classification. The best choice of k relates to the separation of the classes as measured by the average number of correct statements made for an individual assigned to a class to which it does not belong. The maximal predictive classifications are compared with previous classifications of the two groups, which seem to be poor predictively (in terms of the characters considered in this study). The results suggest that taxonomists may be more concerned with maximizing class separation rather than with prediction, but many more groups of organisms would need similar study before this view could be held with confidence.
mesh_terms: D000332:Aerobiosis; D000693:Anaerobiosis; D002861:Chromobacterium / Q000145:classification; D004755:Enterobacteriaceae / Q000145:classification*; D007709:Klebsiella / Q000145:classification*; D012705:Serratia / Q000145:classification; D015003:Yeasts / Q000145:classification* / Q000254:growth & development / Q000378:metabolism