Enhanced tree-classifier performance by inversion with application to pap smear screening data

E. T. Y. Chen; James Lee; Alan C. Nelson

doi:10.1117/12.148673

29 July 1993 Enhanced tree-classifier performance by inversion with application to pap smear screening data

E. T. Y. Chen, James Lee, Alan C. Nelson

Proceedings Volume 1905, Biomedical Image Processing and Biomedical Visualization; (1993) https://doi.org/10.1117/12.148673
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1993, San Jose, CA, United States

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.

Citation Download Citation

E. T. Y. Chen, James Lee, and Alan C. Nelson "Enhanced tree-classifier performance by inversion with application to pap smear screening data", Proc. SPIE 1905, Biomedical Image Processing and Biomedical Visualization, (29 July 1993); https://doi.org/10.1117/12.148673

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