For computing PCA of $X$, do we use the eigenvectors of covariance matrix $X^TX$, or the eigenvectors of kernel matrix $XX^T$ as the principal components?
I am really confused, because seen both used.
For computing PCA of $X$, do we use the eigenvectors of covariance matrix $X^TX$, or the eigenvectors of kernel matrix $XX^T$ as the principal components?
I am really confused, because seen both used.