query: Principal component Analysis : EVD or SVD
positive_passages.docid: 24423
positive_passages.text: What is the difference between "singular value" and "eigenvalue"?
negative_passages.docid: 21224
negative_passages.text: Applying PCA to data that fail a normality test
negative_passages.docid: 117085
negative_passages.text: Linear Discriminant Analysis for $p=1$
negative_passages.docid: 107608
negative_passages.text: Differentiation in support vector machine
negative_passages.docid: 111066
negative_passages.text: Statistical criteria for signal registration
negative_passages.docid: 6206
negative_passages.text: How does centering make a difference in PCA (for SVD and eigen decomposition)?
negative_passages.docid: 49582
negative_passages.text: How to visualize what canonical correlation analysis does (in comparison to what principal component analysis does)?
negative_passages.docid: 29381
negative_passages.text: How to perform dimensionality reduction with PCA in R
negative_passages.docid: 74683
negative_passages.text: Computationally efficient estimation of multivariate mode
negative_passages.docid: 115584
negative_passages.text: Dataset transformation for clustering after PCA
negative_passages.docid: 45832
negative_passages.text: What is the relation between k-means clustering and PCA?
negative_passages.docid: 13726
negative_passages.text: What is the intuition behind SVD?
negative_passages.docid: 25410
negative_passages.text: What is an intuitive explanation for how PCA turns from a geometric problem (with distances) to a linear algebra problem (with eigenvectors)?
negative_passages.docid: 143679
negative_passages.text: Is the sign of principal components meaningless?
negative_passages.docid: 11188
negative_passages.text: Can principal component analysis be applied to datasets containing a mix of continuous and categorical variables?
negative_passages.docid: 87635
negative_passages.text: Why cannot I obtain a valid SVD of X via eigenvalue decomposition of XX' and X'X?
negative_passages.docid: 143724
negative_passages.text: Is it possible to use kernel PCA for feature selection?