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A new shifting grid clustering algorithm
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DOI：10.1016/j.patcog.2003.08.014.png)
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Abstract
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A new density- and grid-based type clustering algorithm using the concept of shifting grid is proposed. The proposed algorithm is a non-parametric type, which does not require users inputting parameters. It divides each dimension of the data space into certain intervals to form a grid structure in the data space. Based on the concept of sliding window, shifting of the whole grid structure is introduced to obtain a more descriptive density profile. As a result, we are able to enhance the accuracy of the results. Compared with many conventional algorithms, this algorithm is computational efficient because it clusters data in a way of cell rather than in points. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Keywords:
clustering
shifting grid
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