25 September 2003 Hierarchical partition scheme in feature space for multivariate clustering
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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539882
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China
Abstract
In this article we propose a hierarchical partition of the feature space based on statistical information on each dimension, and then use mean-shift to properly fuse the obtained super-cubics to reveal the genuine data structure. It not only greatly reduces calculation, but also provides a desirable priori knowledge for bandwidth selection.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai Zhang, Ming Tang, Hanqing Lu, "Hierarchical partition scheme in feature space for multivariate clustering", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539882; https://doi.org/10.1117/12.539882
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