For PCA using the eigenvectors of the covariance matrix, what is the meaning of the eigenvalues?
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When doing a PCA using the largest eigenvectors associated with the largest eigenvalues, what does the values of the eigenvalues means?
Example:
The 2 largest eigenvectors of my dataset are these:
1 - [ 6.62257875e-01 -1.63390189e-01 7.31243512e-01 -1.13386505e-04 -9.65364160e-05 1.02781966e-03]
2 - [ 3.31219165e-01 -8.11563370e-01 -4.81309165e-01 4.26282496e-04 3.70709031e-05 2.55801611e-04]
How can I associate these values with the large dispersion of the data in a plot?
4 commentaires
John D'Errico
le 30 Mai 2020
Modifié(e) : John D'Errico
le 30 Mai 2020
Rather demanding are you? Sorry, but yours is not even a question about MATLAB. I gave you a link that explains PCA. Do you expect us to teach a statistics course in this forum? I'll give you an entire textbook on the subject. I've seen courses taught.
Do some reading.
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