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Feature Selection With Redundancy-Constrained Class Separability

Zhou, Luping; Wang, Lei; Shen, Chunhua


Scatter-matrix-based class separability is a simple and efficient feature selection criterion in the literature. However, the conventional trace-based formulation does not take feature redundancy into account and is prone to selecting a set of discriminative but mutually redundant features. In this brief, we first theoretically prove that in the context of this trace-based criterion the existence of sufficiently correlated features can always prevent selecting the optimal feature set. Then, on...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Journal article
Source: IEEE Transactions on Neural Networks
DOI: 10.1109/TNN.2010.2044189


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