Density‐based clustering

@article{Kriegel2011DensitybasedC,
  title={Density‐based clustering},
  author={Hans-Peter Kriegel and Peer Kr{\"o}ger and J{\"o}rg Sander and Arthur Zimek},
  journal={Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
  year={2011},
  volume={1}
}
  • H. Kriegel, P. Kröger, +1 author A. Zimek
  • Published 2011
  • Computer Science
  • Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Clustering refers to the task of identifying groups or clusters in a data set. In density‐based clustering, a cluster is a set of data objects spread in the data space over a contiguous region of high density of objects. Density‐based clusters are separated from each other by contiguous regions of low density of objects. Data objects located in low‐density regions are typically considered noise or outliers. © 2011 John Wiley & Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 231–240 DOI: 10… Expand
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