Spectral clustering: Difference between revisions

Revision as of 16:39, 30 March 2021

Revision as of 07:00, 13 April 2021

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[[File:6n-graf2.svg|thumb|An example of two connected graphs]]

In [[multivariate statistics]] and the [[cluster analysis|clustering]] of data, '''spectral clustering''' techniques make use of the [[Spectrum of a matrix|spectrum]] ([[eigenvalues]]) of the [[similarity matrix]] of the data to perform [[dimensionality reduction]] before clustering in fewer dimensions. The similarity matrix is provided as an input and consists of a quantitative assessment of the relative similarity of each pair of points in the dataset.

In application to image segmentation, spectral clustering is known as [[segmentation-based object categorization]].