Aimed at the problem that the Quick Shift algorithm needs to manually specify the field value in the migration process,which leads to poor performance on complex datasets,an improved shared nearest neighbor density clustering algorithm(QS-SNN)is proposed.The proposed algorithm was based on shared nearest neighbors(SNN).It calculated the similarity of each pair of points in the dataset,obtained the local density matrix of the sample points through the similarity measurement.The sample points were quickly shift in the SNN field,so that the final clustering result was obtained.Experiments on multiple data sets show that the QS-SNN algorithm has a greater improvement in accuracy than the traditional Quick shift algorithm and other clustering algorithms.
关键词
密度聚类/共享近邻/快速漂移
Key words
Density clustering/Shared-nearest-neighbors/Quick shift
维普
万方数据