An Actual Survey of Dimensionality Reduction

Abstract

Dimension reduction is defined as the processes of projecting high-dimensional data to a much lower-dimensional space. Dimension reduction methods variously applied in regression, classification, feature analysis and visualization. In this paper, we review in details the last and most new version of methods that extensively developed in the past decade.

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Sarveniazi, A. (2014) An Actual Survey of Dimensionality Reduction. American Journal of Computational Mathematics, 4, 55-72. doi: 10.4236/ajcm.2014.42006.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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