PCA on a 3d Matrix
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Micheal Dennington on 20 Jun 2020
Commented: Sanchay Mukherjee on 31 Jan 2022
Hi. I have a data set of http://www.ehu.eus/ccwintco/index.php/Hyperspectral_Remote_Sensing_Scenes Indian Pines. Data set is a 145x145x200 matrix that 145x145 represents spatial dimensions, 200 represents feature dimensions. I wnat to do PCA dimension reduction but I can't figure out how to deal 3d matrix. If you could help me I would be appreciated. Thanks.
Sanchay Mukherjee on 31 Jan 2022
Did you figure out hte solution? I am trying to do a similar thing. I have a matrix of 200*500*3, where 200*500 is the data for corresponding 3 features.
Subhadeep Koley on 16 Nov 2020
You can use the hyperpca function to achieve the same.
% Definenumber of principal components you require
numComponents = 10;
% Perform PCA transform
outputDataCube = hyperpca(indianPinesMatrix, numComponents);
The above mentioned feture comes under Image Processing Toolbox's Hyperspectral Imaging Library support package, and can be downloaded from here. For more information on Hyperspectral Imaging Library see the documentation.
Find more on Dimensionality Reduction and Feature Extraction in Help Center and File Exchange
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