Why should one scale variables before performing PCA?
6316
PCA on correlation or covariance?
49535
Deep learning : How do I know which variables are important?
22551
What can cause PCA to worsen results of a classifier?
9488
When conducting multiple regression, when should you center your predictor variables & when should you standardize them?
9663
Is it a good practice to always scale/normalize data for machine learning?
97435
Reversing PCA back to the original variables
113464
When dealing with rasters of varying resolutions should one resample to the highest or lowest resolution?
82715
Scale parameters -- How do they work, why are they sometimes dropped?
70917
What's the difference between principal component analysis and multidimensional scaling?
21224
Applying PCA to data that fail a normality test
114794
Is there any advantage of SVD over PCA?
154757
One component in PCA is always the mean vector in two-dimensions but not three
48892
whether to rescale indicator / binary / dummy predictors for LASSO
81049
What norm of the reconstruction error is minimized by the low-rank approximation matrix obtained with PCA?
14465
"Normalizing" variables for SVD / PCA
6206
How does centering make a difference in PCA (for SVD and eigen decomposition)?
55662
How to use principal components analysis to select variables for regression?