Machine learning
DBSCAN
DBSCAN 是一种基于密度的聚类算法，由 Ester、Kriegel、Sander 和 Xu 于 1996 年提出，它将位于密集区域的点分组，并将稀疏区域的点标记为噪声。该算法能有效处理含噪声的数据以及形状不规则、非球状的簇。
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来源
- Ester, M., Kriegel, H.-P., Sander, J. & Xu, X. (1996). A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. Proceedings of the 2nd KDD, 226–231. link ↗
如何引用本页
ScholarGate. (2026, June 1). DBSCAN (Density-Based Spatial Clustering of Applications with Noise). ScholarGate. https://scholargate.app/zh/machine-learning/dbscan
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