On clustering with chernoff-type faces
Chernoff (1973) introduced a new procedure for representing multidimensional data by using cartoon-like faces drawn by a pen plotter, while Turner and Tidmore (1977) introduced asyrimetric Chernoff-type faces which can be generated on a line printer. The use of such faces for clustering multivariate data is a well known technique. However, there have been few attempts, to evaluate this graphical procedure in a systematic fashion. This paper reports results obtained in a comparison of the 1ine printer faces clustering method with several nongraphical hierarchical clustering algorithms, including single , compete , and average linkage and Ward's minimum variance method..