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- W2807146096 abstract "Density peaks clustering algorithm (DPC) is a new density-based clustering algorithm proposed to obtain any shape of the clusters. It finds cluster centers according to the decision graph which drawn based on the density-distance. However, in the process of calculating local density and distance of each point, the time complexity is O(n^2), which limits the application of DPC. In this paper, we propose a fast density peaks clustering algorithm based on pre-screening (PDPC), which can effectively reduce the calculation complexity on the basis of ensuring the accuracy of clustering. According to the uneven distribution of data sets, the novel pre-screening method is used to remove some points with sparse local density first, and then the cluster centers are selected by using the decision graph. Theoretical analysis and experimental results show that this algorithm can not only reduce the time complexity, but also cluster correctly." @default.
- W2807146096 created "2018-06-13" @default.
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- W2807146096 date "2018-01-01" @default.
- W2807146096 modified "2023-09-23" @default.
- W2807146096 title "A Fast Density Peaks Clustering Algorithm Based on Pre-Screening" @default.
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- W2807146096 doi "https://doi.org/10.1109/bigcomp.2018.00084" @default.
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