Meaning of principal components
158823
Principal component analysis "backwards": how much variance of the data is explained by a given linear combination of the variables?
7632
Interpretation of biplots in principal components analysis
157062
Dimensionality reduction (SVD or PCA) on a large, sparse matrix
55662
How to use principal components analysis to select variables for regression?
34539
How to intuitively understand eigenvalue and eigenvector?
79786
How would PCA help with a k-means clustering analysis?
64432
Physical or geometric meaning of the trace of a matrix
102317
Is there a geometrical interpretation to the notion of eigenvector and eigenvalues?
36609
Creating a single index from several principal components or factors retained from PCA/FA
139690
Which variables should I transform, center, and/or standardize in my data for Principal Component Analysis?
88975
I need an intuitive explanation of eigenvalues and eigenvectors
49582
How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
154757
One component in PCA is always the mean vector in two-dimensions but not three
154304
Do PCA affect different classification methods?
3089
Why PCA of data by means of SVD of the data?
154261
PCA when the dimensionality is greater than the number of samples
143679
Is the sign of principal components meaningless?