Diagonally Colorized iVAT Images for Labeled Data

Abstract

The iVAT (improved Visual Assessment of cluster Tendency) image is a useful tool for assessing possible cluster structure in an unlabeled, numerical data set. If labeled data are available then it is sometimes helpful to determine how closely the (unlabeled) data clusters agree with the data partitioning based on the labels. In this note the DCiVAT (Diagonally Colorized iVAT) image is introduced for the case of labeled data. It incorporates all available data and label information into a single colorized iVAT image so that it is possible to visually assess the degree to which data clusters are aligned with label categories. The new approach is illustrated with several examples.