Journal of the Korean Data and Information Science Society
- Volume 18 Issue 4
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- Pages.1135-1143
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- 2007
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- 1598-9402(pISSN)
The Comparison of Singular Value Decomposition and Spectral Decomposition
Abstract
The singular value decomposition and the spectral decomposition are the useful methods in the area of matrix computation for multivariate techniques such as principal component analysis and multidimensional scaling. These techniques aim to find a simpler geometric structure for the data points. The singular value decomposition and the spectral decomposition are the methods being used in these techniques for this purpose. In this paper, the singular value decomposition and the spectral decomposition are compared.
Keywords
- Multidimensional Scaling;
- Principal Component Analysis;
- Singular Value Decomposition;
- Spectral Decomposition