Density of clustering algorithm based on relative distance
基于相对距离的密度聚类算法*

This paper firstly introduced the shortage of the traditional method in calculating the deficiencies in the application of clustering. To address this shortcoming, put forward a relative distance calculation method based on the weighted vector. The algorithm was based on the DBSCAN algorithm, and integrated of the calculation of relative distance and the application of the scope finding of the k-d tree. The algorithm can not only be good clustering effect, and the elimination of the unit of measurement data on the impact of cluster results.