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The spectral clustering algorithm, which cluster by using the eigenvalues and eigenvectors of Laplacian matrix, may not be obtained the desired clustering results in some cases. It is possible to remedy this deficiency by using the singular value decomposition (SVD) in the spectral clustering algorithm. It is presented in this article the algorithm of spectral clustering based on SVD which use singular...
The spectral clustering algorithm's space complexity is O(n2), while time complexity is O(n3). When dealing with large amounts of data, the memory will overflow and run-time is too long. For the general problem of spectral clustering, if the clustering data of sub-problem between the original problem has the same probability distribution, it can be applied to divide and conquer strategy for the problem...
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