NDLI: Non-negative sparse subspace clustering by orthogonal matching pursuit

Content Provider	IET Digital Library
Author	Zhan, Jiaqiyu Bai, Zhiqiang Zhu, Yuesheng
Abstract	In sparse subspace clustreing (SSC), non-zero coefficients in the sparse representations are transformed to positive values to construct the affinity matrix. However, negative coefficients are not supposed to cause positive correlation in nature, so that the clustering performance may be undermined. In this Letter, non-negative SSC by orthogonal matching pursuit (nSSCOMP) with a negative re-purpose module is introduced for a reasonable clustering graph to improve the clustering performance, also an assemble negatives of negatives algorithm is proposed to strengthen the effectiveness of affinity matrix. The analysis indicates that the authors' approach can make the coefficient matrix contains only non-negative values and bring additional positive correlations. Their approach is the first to process negative values after sparse representations are already calculated, without specify non-negativity constraints beforehand. Experimental results demonstrate with the nSSCOMP not only the clustering accuracy and subspace-preserving property can be improved, but also time complexity be kept.
Starting Page	137
Ending Page	139
Page Count	3
ISSN	00135194
Volume Number	56
e-ISSN	1350911X
Issue Number	Issue 3, Feb (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/56/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2019.3066
Journal	Electronics Letters
Publisher Date	2019-11-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Affinity Matrix Assemble Negatives Clustering Accuracy Clustering Graph Clustering Performance Coefficient Matrix Combinatorial Mathematics Data Handling Technique Graph Theory Interpolation And Function Approximation Iterative Method Linear Algebra Negative Coefficient Negative Re-purpose Module Negatives Algorithm Nonnegative Sparse SubSpace Clustering Nonnegative SSC Nonnegativity Constraint NSSCOMP Numerical Analysis Orthogonal Matching Pursuit Algorithm Pattern Clustering Positive Correlation Sparse Matrix Sparse Representations SubSpace-preserving Property
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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