Variable Selection using Principal Component Analysis
26181
Using principal component analysis (PCA) for feature selection
114625
Model selection and cross-validation: The right way
103531
Feature Selection Packages in R, which do both regression and classification
145172
Objective function of canonical correlation analysis (CCA)
36609
Creating a single index from several principal components or factors retained from PCA/FA
53330
Lasso and statistical signficance of selected variables
126726
PCA, LDA, CCA, and PLS
104236
Factor analysis and regression
6316
PCA on correlation or covariance?
154304
Do PCA affect different classification methods?
44881
Using lasso for feature selection, followed by a non-regularized regression
17025
What exactly is called "principal component" in PCA?
18487
Why are there only $n-1$ principal components for $n$ data if the number of dimensions is $\ge n$?
10466
Making sense of principal component analysis, eigenvectors & eigenvalues
13787
Why log-transforming the data before performing principal component analysis?
142959
Do we still need to do feature selection while using Regularization algorithms?
20101
What are disadvantages of using the lasso for variable selection for regression?