2
$\begingroup$

can you please tell me why eigenvalues are used in PCA. Specifically why and how does it explain the variance of the components

$\endgroup$
0
$\begingroup$

I believe that PCA is one of the most well-suited applications of eigenvector/eigenvalues.

I found a good youtube video that explain PCA well.

To explain coupling, think of two variables, area,$A$ and perimeter,$P$ of a rectangle. We know that $A = width * height$ and $P = 2(width+height)$. Thus we can say that $A$ and $p$ is coupled with $width$ and $height$ of the rectangle, changing $A$ will also change $p$ because of the change of $width$ and $height$. Though the example I given is not linear, you can get the idea.

| cite | improve this answer | |
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.