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Gda

Generalized Discriminant Analysis (GDA) - non-linear feature dimensionality reduction technique

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/learn @mhaghighat/Gda
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Quality Score

0/100

Supported Platforms

Zed

README

Generalized Discriminant Analysis

GDA Performs Generalized Discriminant Analysis, a non-linear feature dimensionality reduction technique.

GDA is one of dimensionality reduction techniques, which projects a data matrix from a high-dimensional space into a low-dimensional space by maximizing the ratio of between-class scatter to within-class scatter.

More details can be found in Section 4.3 of:

M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, "CloudID: Trustworthy cloud-based and cross-enterprise biometric identification," Expert Systems with Applications, vol. 42, no. 21, pp. 7905-7916, 2015. http://dx.doi.org/10.1016/j.eswa.2015.06.025

(C) Mohammad Haghighat, University of Miami haghighat@ieee.org PLEASE CITE THE ABOVE PAPER IF YOU USE THIS CODE.

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GitHub Stars19
CategoryDevelopment
Updated25d ago
Forks7

Languages

Matlab

Security Score

90/100

Audited on Mar 12, 2026

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