The dissimilarity representation as a tool for three-way data classification: a 2D measure

Abstract. The dissimilarity representation has demonstrated advan-tages in the solution of classification problems. Meanwhile, the repre-sentation of objects by multi-dimensional arrays is necessary in many research areas. However, the development of proper classification tools that take the multi-way structure into account is incipient. This paper introduces the use of the dissimilarity representation as a tool for classi-fying three-way data, as dissimilarities allow the representation of multi-dimensional objects in a natural way. As an example, the classification of three-way seismic volcanic data is used. A comparison is made between dissimilarity measures used in different representations of the three-way data. 2D dissimilarity measures for three-way data can be useful