How does eigenvalues measure variance along the principal components in PCA?
25410
What is an intuitive explanation for how PCA turns from a geometric problem (with distances) to a linear algebra problem (with eigenvectors)?
85455
Does Eigenvalues evaluate in a parallelized way?
101622
Choosing number of principal components to retain
158823
Principal component analysis "backwards": how much variance of the data is explained by a given linear combination of the variables?
67557
Imputation of missing values for PCA
139557
Why are the eigenvectors of the Laplacian of a ring graph sinusoidal?
14465
"Normalizing" variables for SVD / PCA
24814
Is PCA still done via the eigendecomposition of the covariance matrix when dimensionality is larger than the number of observations?
55662
How to use principal components analysis to select variables for regression?
93325
Difference In Eigenvectors
115467
Eigenvalues of Householder matrix
49582
How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
135047
Why does PCA maximize total variance of the projection?
41608
Weighted principal components analysis
56670
The intuition behind generalized eigenvectors
156166
PCA of non-Gaussian data
6590
PCA and proportion of variance explained