A Density Clustering Algorithm Based on Data Partitioning
نویسنده
چکیده
As a density clustering algorithm, DBSCAN can find the denser part of data-centered samples, and generalize the category in which sample is relatively centered. This article analyzes the traditional DBSCAN clustering algorithm and its flaw, and discusses an implementation of a density clustering algorithm based on data partitioning. The algorithm can solve the memory support and I/O consuming problems when it handles high volume data, and gets faster clustering speed and the best clustering effect.
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