A Modified Spectral Clustering Algorithm Based on NJW
Biao Huang, Peng Yang · 2008
Spectral clustering has become one of the most popular modern clustering algorithms because it has "global" optimal solution compared with traditional clustering methods. In this paper, we propose a modified NJW algorithm which is based on matrix perturbation theory and can be easily implemented. In addition, the algorithm can estimate the parameter k and in turn achieve appropriate clusters. The experimental results on a number of challenging clustering problems show that it has good performance.