PCA for dimension reduction in 1D data

Version 1.0.0 (2.05 KB) by Selva
using principal component analysis for dimension reduction of feature vector in the SVM classification problem


Updated 28 Sep 2018

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PCA is used for projecting data matrix from higher dimension to lower dimension

Cite As

Selva (2023). PCA for dimension reduction in 1D data (https://www.mathworks.com/matlabcentral/fileexchange/68942-pca-for-dimension-reduction-in-1d-data), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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