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Among different clustering techniques, including Centroid-based, Graph-based, and Density-based, the Density-Based Clustering Methods received lots of attentions.
Basic idea of density-based clustering is that Clusters are dense regions in the data space, separated by regions of lower object density. These methods could be great since they are able to:
- Discover clusters of arbitrary shape
- Handle noise
- One scan
However, it should be mentioned that these methods Need density parameters.
Here two interesting studies over the years: DBSCAN is the first density-based clustering proposed in 1996 and recently the density peak clustering DPC proposed in 2014. |
IEEE/ICACT20230188 Slide.03
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