Principal Component Analysis handled multicolinearity in data
10466
Making sense of principal component analysis, eigenvectors & eigenvalues
103877
The advantages and disadvantages of using Kaiser Rule to select the number of principal components
7442
completing the square for Gaussian multivariate estimation
152420
Robust PCA vs. robust Mahalanobis distance for outlier detection
154304
Do PCA affect different classification methods?
74683
Computationally efficient estimation of multivariate mode
158716
Cholesky versus eigendecomposition for drawing samples from a multivariate normal distribution
7328
The proof of shrinking coefficients using ridge regression through "spectral decomposition"
117085
Linear Discriminant Analysis for $p=1$
46319
How to perform orthogonal regression (total least squares) via PCA?
26181
Using principal component analysis (PCA) for feature selection
4244
How to compute PCA scores from eigendecomposition of the covariance matrix?
14181
Can averaging all the variables be seen as a crude form of PCA?
7779
How does centering the data get rid of the intercept in regression and PCA?
81049
What norm of the reconstruction error is minimized by the low-rank approximation matrix obtained with PCA?
93145
Can I add several additional variables to my principal component regression?
126886
Do the principal components change if we apply PCA more than once (recursively) on data?