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Proceedings Paper

Enhanced tree-classifier performance by inversion with application to pap smear screening data
Author(s): E. T. Y. Chen; James Lee; Alan C. Nelson
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Paper Abstract

In this paper, we present an inversion method to enhance a binary decision tree classifier using boundary search of training samples. We want to enhance the training at those points which are close to the boundaries. Selection of these points is based on the Euclidean distance from those centroids close to classification boundaries. The enhanced training using these selected data was compared with training using randomly selected samples. We also applied this method to improve the classification of pap smear screening data.

Paper Details

Date Published: 29 July 1993
PDF: 6 pages
Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); doi: 10.1117/12.148673
Show Author Affiliations
E. T. Y. Chen, Univ. of Washington (United States)
James Lee, Univ. of Washington (United States)
Alan C. Nelson, NeoPath Inc. (United States)

Published in SPIE Proceedings Vol. 1905:
Biomedical Image Processing and Biomedical Visualization
Raj S. Acharya; Dmitry B. Goldgof, Editor(s)

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