Conference Proceedings
Extension of iVAT to asymmetric matrices
TC Havens, JC Bezdek, C Leckie, M Palaniswami
IEEE International Conference on Fuzzy Systems | IEEE | Published : 2013
Abstract
The iVAT algorithm reorders (symmetric) dissimilarity data so that an image of the data may reveal cluster substructure. This paper extends the method so that it can handle asymmetric dissimilarity data. The extension is based on replacing the asymmetric input data with its unique least-squared error approximation by a symmetric matrix. Examples are given to illustrate the new method, called asymmetric iVAT (asiVAT). © 2013 IEEE.
Grants
Funding Acknowledgements
This material is based on work supported by the Australian Research Council.