Everything about DBSCAN
Density-based data clustering algorithm
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. It is a density-based clustering algorithm that does not assume a fixed parametric model for the clusters, such as Gaussian blobs, and it does not require the number of clusters to be specified in advance. Given a set of points in some space, it groups together points that are closely packed, and marks as outliers points that lie alone in low-density regions . DBSCAN is one of the most commonly used and cited clustering algorithms. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: DBSCANA 5-minute orientation
- Skim a recent paper: An approach to boundary detection for 3D point clouds based on DBSCAN clusteringInfluential work since 2022
- Read the landmark paper: DBSCAN Revisited, RevisitedCited 2,722 times
- Go sideways: OPTICS algorithmA closely related topic
- Go sideways: Local outlier factorA closely related topic
📖 Definitions
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🏆 Landmark papers (most cited)
DBSCAN Revisited, Revisited
ST-DBSCAN: An algorithm for clustering spatial–temporal data
dbscan: Fast Density-Based Clustering with R
Real-Time Superpixel Segmentation by DBSCAN Clustering Algorithm
A fast DBSCAN clustering algorithm by accelerating neighbor searching using Groups method
Revised DBSCAN algorithm to cluster data with dense adjacent clusters
RNN-DBSCAN: A Density-Based Clustering Algorithm Using Reverse Nearest Neighbor Density Estimates
DSets-DBSCAN: A Parameter-Free Clustering Algorithm
🆕 Influential since 2022
An approach to boundary detection for 3D point clouds based on DBSCAN clustering
RN-SMOTE: Reduced Noise SMOTE based on DBSCAN for enhancing imbalanced data classification
A DBSCAN-based automated operational modal analysis algorithm for bridge monitoring
A fast DBSCAN algorithm for big data based on efficient density calculation
Intelligent mapping of geochemical anomalies: Adaptation of DBSCAN and mean-shift clustering approaches
📚 Books worth reading
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🔗 Related topics
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