Using PCA to reduce dimensionality of training and testing data
2632
PCA and the train/test split
154261
PCA when the dimensionality is greater than the number of samples
81049
What norm of the reconstruction error is minimized by the low-rank approximation matrix obtained with PCA?
22551
What can cause PCA to worsen results of a classifier?
84446
How to project a new vector onto PCA space?
45832
What is the relation between k-means clustering and PCA?
67557
Imputation of missing values for PCA
145064
Techniques to detect overfitting
55662
How to use principal components analysis to select variables for regression?
17765
How to use SVD for dimensionality reduction to reduce the number of columns (features) of the data matrix?
4244
How to compute PCA scores from eigendecomposition of the covariance matrix?
104438
Random Forest mtry Spit-to-Split Variable Sampling Procedure
103877
The advantages and disadvantages of using Kaiser Rule to select the number of principal components
126726
PCA, LDA, CCA, and PLS
55847
PCA demeaning the data
154304
Do PCA affect different classification methods?
7632
Interpretation of biplots in principal components analysis