Modularity Component Analysis versus Principal Component Analysis
American Journal of Applied Mathematics
Volume 4, Issue 2, April 2016, Pages: 99-104
Received: Apr. 6, 2016; Published: Apr. 11, 2016
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Authors
Hansi Jiang, North Carolina State University, Raleigh, NC, USA
Carl Meyer, North Carolina State University, Raleigh, NC, USA
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Abstract
In this paper the exact linear relation between the leading eigenvectors of the modularity matrix and the singular vectors of an uncentered data matrix is developed. Based on this analysis the concept of a modularity component is defined, and its properties are developed. It is shown that modularity component analysis can be used to cluster data similar to how traditional principal component analysis is used except that modularity component analysis does not require data centering.
Keywords
Data Clustering, Graph Partitioning, Modularity Matrix, Principal Component Analysis
To cite this article
Hansi Jiang, Carl Meyer, Modularity Component Analysis versus Principal Component Analysis, American Journal of Applied Mathematics. Vol. 4, No. 2, 2016, pp. 99-104. doi: 10.11648/j.ajam.20160402.15
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