PCA demonstration and tool

Version 1.0.3 (2.59 KB) by Lyes Demri
This is just a small demo of PCA and includes a function to encode a data matrix with the smallest amount of dimensions
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Updated 11 Sep 2023

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PCA_demo.m is a demonstration of Principal Component Analysis in action and is based on Ian Goodfellow's Deep Learning Book.
PCA.m is a function that will reduce the data you feed it using the smallest amount of dimensions necessary to represent it while preserving a reconstruction error below a threshold you can choose.

Cite As

Lyes Demri (2026). PCA demonstration and tool (https://uk.mathworks.com/matlabcentral/fileexchange/135141-pca-demonstration-and-tool), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.3

Fixed exit criterion
1.0.2

Fixed output such that each point is a row of c (instead of a column)
1.0.1

Added varargin to PCA function
1.0.0