When using principal components as predictors in linear regression, PC1 comes out not significant
52047
How can top principal components retain the predictive power on a dependent variable (or even lead to better predictions)?
81049
What norm of the reconstruction error is minimized by the low-rank approximation matrix obtained with PCA?
16641
Strange results of varimax rotation of principal component analysis in Stata: rotated components are all zeros and ones
36565
Box-Cox transformation vs. predictor transformation in multiple linear regression
55847
PCA demeaning the data
106596
Why L1 norm for sparse models
6206
How does centering make a difference in PCA (for SVD and eigen decomposition)?
50490
Why do the R functions 'princomp' and 'prcomp' give different eigenvalues?
24814
Is PCA still done via the eigendecomposition of the covariance matrix when dimensionality is larger than the number of observations?
6590
PCA and proportion of variance explained
79786
How would PCA help with a k-means clustering analysis?
97758
Is using correlation matrix to select predictors for regression correct?
22551
What can cause PCA to worsen results of a classifier?
112134
What are principal component scores?
13787
Why log-transforming the data before performing principal component analysis?
10466
Making sense of principal component analysis, eigenvectors & eigenvalues
90089
Why are PCA eigenvectors orthogonal and what is the relation to the PCA scores being uncorrelated?