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14 December 2015 A modified density-based clustering algorithm and its implementation
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Proceedings Volume 9813, MIPPR 2015: Pattern Recognition and Computer Vision; 98130E (2015) https://doi.org/10.1117/12.2204778
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
This paper presents an improved density-based clustering algorithm based on the paper of clustering by fast search and find of density peaks. A distance threshold is introduced for the purpose of economizing memory. In order to reduce the probability that two points share the same density value, similarity is utilized to define proximity measure. We have tested the modified algorithm on a large data set, several small data sets and shape data sets. It turns out that the proposed algorithm can obtain acceptable results and can be applied more wildly.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhihua Ban, Jianguo Liu, Lulu Yuan, and Hua Yang "A modified density-based clustering algorithm and its implementation", Proc. SPIE 9813, MIPPR 2015: Pattern Recognition and Computer Vision, 98130E (14 December 2015); https://doi.org/10.1117/12.2204778
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