Computing eigenvectors for PCA

r
pca
data_wrangling

#1

I came to know about the following steps in doing PCA:

  1. Given some data matrix X,subtract the mean from each dimension.
  2. Calculate the sample covariance matrix.
  3. Calculate the eigen vectors and values of the covariance.
  4. Keep the vectors with the largest values.(W)
  5. Derive the reduced data matrix Z = XW.

Can somebody please explain these points with a practical example in R?


#2

@shuvayan- you can check on this link.
http://www2.stat.unibo.it/montanari/Didattica/Multivariate/PCA_lab1.pdf.

Hope this helps!
Regards,
Rohit


#3

Hello @hinduja1234,

Thanks for the link.But I am having difficulty in understanding PCA from there.Can you please point me towards something more simple yet illustrative.
Thanks!