Class proximity measures - Dissimilarity-based classification and display of high-dimensional data

Authors:
R. L. Somorjai;B. Dolenko;A. Nikulin;W. Roberson;N. Thiessen
Affiliations:
Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6;Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6;Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6;Institute for Biodiagnostics, National Research Council Canada, 435 Ellice Avenue, Winnipeg, MB, Canada R3B 1Y6;Genome Sciences Centre, BC Cancer Agency, 570 West 7th Ave. - Suite 100, Vancouver, BC, Canada V5Z 4S6
Venue:
Journal of Biomedical Informatics
Year:
2011

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Abstract

For two-class problems, we introduce and construct mappings of high-dimensional instances into dissimilarity (distance)-based Class-Proximity Planes. The Class Proximity Projections are extensions of our earlier relative distance plane mapping, and thus provide a more general and unified approach to the simultaneous classification and visualization of many-feature datasets. The mappings display all L-dimensional instances in two-dimensional coordinate systems, whose two axes represent the two distances of the instances to various pre-defined proximity measures of the two classes. The Class Proximity mappings provide a variety of different perspectives of the dataset to be classified and visualized. We report and compare the classification and visualization results obtained with various Class Proximity Projections and their combinations on four datasets from the UCI data base, as well as on a particular high-dimensional biomedical dataset.