Description Usage Arguments Value References Examples

View source: R/SpectralClustering.R

Finding optimal discrete solutions for spectral clustering

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`Y` |
a matrix with N rows and K columns, with N being the number of objects (e.g., patients), K being the number of clusters. The K columns of 'Y' should correspond to the first k eigenvectors of graph Laplacian matrix (of affinity matrix) corresponding to the k smallest eigenvalues |

`verbose` |
logical(1); if true, print some information |

class assignment matrix with the same shape as Y (i.e., N x K). Each row contains all zeros except one 1. For instance, if X_ij = 1, then object (eg, patient) i belongs to cluster j.

Stella, X. Yu, and Jianbo Shi. "Multiclass spectral clustering." ICCV. IEEE, 2003.

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