Extension of iVAT to asymmetric matrices
Document Type
Conference Proceeding
Publication Date
11-22-2013
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.
Publication Title
IEEE International Conference on Fuzzy Systems
Recommended Citation
Havens, T.,
Bezdek, J.,
Leckie, C.,
&
Palaniswami, M.
(2013).
Extension of iVAT to asymmetric matrices.
IEEE International Conference on Fuzzy Systems.
http://doi.org/10.1109/FUZZ-IEEE.2013.6622300
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/10477