Extension of iVAT to asymmetric matrices
Timothy Craig Havens, James C. Bezdek, Christopher A. Leckie, Marimuthu Swami Palaniswami · 2013
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).