Spectral Clustering
Spectral Clustering
Spectral clustering has attracted increasing attention due to
the promising ability in dealing with nonlinearly separable datasets [15], [16]. In spectral clustering, the spectrum of the graph Laplacian is used to reveal the cluster structure. The spectral clustering algorithm mainly consists of two steps: 1) constructs the low dimensional embedded representation of the data based on the eigenvectors of the graph Laplacian, 2) applies k-means on the constructed low dimensional data to obtain the clustering result. Thus,
A Tutorial on Spectral Clustering
https://paperswithcode.com/paper/a-tutorial-on-spectral-clustering
A Tutorial on Spectral Clustering