Clustering via kernel decomposition

IEEE Trans Neural Netw. 2006 Jan;17(1):256-64. doi: 10.1109/TNN.2005.860840.

Abstract

Spectral clustering methods were proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this letter, the affinity matrix is created from the elements of a nonparametric density estimator and then decomposed to obtain posterior probabilities of class membership. Hyperparameters are selected using standard cross-validation methods.

Publication types

  • Letter