Search results with tag "Spectral clustering and normalized cuts"

Kernel k-means, Spectral Clustering and Normalized Cuts

approach is spectral clustering algorithms, which use the eigenvectors of an affinity matrix to obtain a clustering of the data. A popular objective function used in spectral clus-tering is to minimize the normalized cut [12]. On the surface, kernel k-means and spectral clustering appear to be completely different approaches. In this pa-

  Name, Cuts, Spectral, Normalized, Clustering, Spectral clustering and normalized cuts