About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
CSDA
Paper
Class visualization of high-dimensional data with applications
Abstract
The problem of visualizing high-dimensional data that has been categorized into various classes is considered. The goal in visualizing is to quickly absorb inter-class and intra-class relationships. Towards this end, class-preserving projections of the multidimensional data onto two-dimensional planes, which can be displayed on a computer screen, are introduced. These class-preserving projections maintain the high-dimensional class structure, and are closely related to Fisher's linear discriminants. By displaying sequences of such two-dimensional projections and by moving continuously from one projection to the next, an illusion of smooth motion through a multidimensional display can be created. Such sequences are called class tours. Furthermore, class-similarity graphs are overlaid on the two-dimensional projections to capture the distance relationships in the original high-dimensional space. The above visualization tools are illustrated on the classical Iris plant data, the ISOLET spoken letter data, and the PENDIGITS on-line handwriting data set. It is shown how the visual examination of the data can uncover latent class relationships. © 2002 Elsevier Science B.V. All rights reserved.