Title :
Visualizing High Dimensional Datasets Using Partiview
Author :
Surendran, Dinoj ; Levy, Stuart
Author_Institution :
University of Chicago
Abstract :
A standard method of visualizing high-dimensional data is reducing its dimensionality to two or three using some algorithm, and then creating a scatterplot with data represented by labelled and/or colored dots. Two problems with this approach are (1) dots do not represent data well, (2) reducing to just three dimensions does not make full use of several dimensionality-reduction algorithms. We demonstrate how Partiview can be used to solve these problems, in the context of handwriting recognition and image retrieval.
Keywords :
dimensionality reduction; glyphs; high dimensional data visualization; image retrieval; information visualization; optical character recognition; Bioinformatics; Computer graphics; Data visualization; Face recognition; Frequency; Genomics; Hardware; Humans; Image retrieval; Information retrieval;
Conference_Titel :
Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on
Print_ISBN :
0-7803-8779-3
DOI :
10.1109/INFVIS.2004.76