DBSCAN, or density-based spatial clustering of applications with noise, is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jorg Sander and Xiaowei Xu in 1996. It groups together points that are closely packed in a data set while marking as outliers points that lie alone in low density regions, without assuming a fixed model for the shape of a cluster or requiring the number of clusters to be specified in advance. It is one of the most widely used and most cited clustering algorithms in data mining and machine learning.
Facts
Time Complexity
Time Complexity (category)Linearithmic Time -- O(n log n) 1 Time Complexity (category)Quadratic Time -- O(n^2) 1 Connections
Held Differently
BIRCH Algorithm, Algorithms Not a settled lineage claim: BIRCH's own inventors claim priority over DBSCAN as the first database-area clustering algorithm to handle noise effectively. Verified en.wikipedia.org/wiki/BIRCH: "Its inventors claim BIRCH to be the 'first clustering algorithm proposed in the database area to handle noise... effectively', beating DBSCAN by two months."
Credited To
Source DBSCAN (Wikipedia)
Source DBSCAN (Wikipedia)
In Field
Source DBSCAN (Wikipedia)
Invented By
Source DBSCAN (Wikipedia)
Source DBSCAN (Wikipedia)
Predecessor Of
Verified en.wikipedia.org/wiki/OPTICS_algorithm: "Its basic idea is similar to DBSCAN, but it addresses one of DBSCAN's major weaknesses." OPTICS is the later, same-authors extension of DBSCAN.
Sources
1. DBSCAN (Wikipedia)
Wikipedia article body, read for Browse By backfill (w-bbfill-computing6-0927)
DBSCAN (Wikipedia)
Credited To: Hans-Peter Kriegel, Lead section
proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996
Invented By: Hans-Peter Kriegel, Lead section
proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996
Credited To: Martin Ester, Lead section
proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996
Invented By: Martin Ester, Lead section
proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996
In Field: Data Mining, Lead
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996.
In Group: Clustering Algorithms, Lead
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996.
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