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OPTICS-algorithm---Wikipedia--the-free-encycloped
- OPTICS ("Ordering Points To Identify the Clustering Structure") is an algorithm for finding density-based clusters in spatial data. It was presented by Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel and Jö rg Sander[1]. Its basic idea is
DBSCAN---Wikipedia--the-free-encyclopedia
- DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jö rg Sander and Xiaowei Xu in 1996.[1] It is a density-based clustering algorithm because it fi
DBSCAN
- The method of spatial data clustering (using DBSCAN) and applications in the locate optimal ATM (Viet Nam Lang)
DBSCAN
- DBSCAN clustering in vietnamese
Data-Mining
- 本论文在对各种算法深入分析的基础上，尤其在对基于密度的聚类算法、基于层次的聚类算法和基于划分的聚类算法的深入研究的基础上，提出了一种新的基于密度和层次的快速聚类算法。该算法保持了基于密度聚类算法发现任意形状簇的优点，而且具有近似线性的时间复杂性，因此该算法适合对大规模数据的挖掘。理论分析和实验结果也证明了基于密度和层次的聚类算法具有处理任意形状簇的聚类、对噪音数据不敏感的特点，并且其执行效率明显高于传统的DBSCAN算法。-Based on the analysis on clustering