Comparing PCA and Non-negative Matrix Factorization (NNMF)

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In this video, Non-negative Matrix Factorization (NNMF) and Principal Component Analysis (PCA) are compared with each other in terms of their basis functions. They are also compared in terms of compression and subsequent reconstruction of data. To access the code, use the following link:

  1. Morteza
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Комментарии
Автор

Thank you for making this video! It was very helpful!!

markstephen
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NNMF basis functions are not orthogonal with respect to each other, but PCA basis functions are. I mistakenly say that both methods give orthogonal basis functions, which is not correct.

Morteza_Sc
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Unless I'm mistaken, NNMF basis functions are not orthogonal to each other. If I choose any two of your NNMF basis functions and integrate their product wrt wavelength over all defined wavelengths (400 to 700nm), I'll get a value greater than zero.

derekmiddlemiss