New variables after computing Principal Components Analysis

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NCA
NCA 2021-7-5
评论： the cyclist 2021-7-5
After computing principal components analysis, what will represent my new variables to be used to build my model , is it the scores?
Thank You

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the cyclist
the cyclist 2021-7-5
Yes, the output score is the observed values of the variables in the principal coordinate axes.
I wrote a detailed answer to this question that is a tutorial on how to use MATLAB's pca() function. You might find it helpful.
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NCA
NCA 2021-7-5
Thanks a lot for taking the time out to respond and answer my question, I really appreciate. Am I right to only use the first few columns of my scores as shown by 'explained' ( example 80% explained variance) or do I need to use score multiplied by coeff (score*coeff) to build my model?
Thank You
the cyclist
the cyclist 2021-7-5
You want to use score, not score*coeff.
score is equivalent to X*coeff; it's the original observations transformed to the PC coordinates.

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Image Analyst
Image Analyst 2021-7-5
Attached is a demo where I get the PCs of an RGB true color image, plus another demo.

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