query: Are there examples of more informative PCA plots?
positive_passages.docid: 6058
positive_passages.text: Visualizing a million, PCA edition
negative_passages.docid: 45832
negative_passages.text: What is the relation between k-means clustering and PCA?
negative_passages.docid: 143724
negative_passages.text: Is it possible to use kernel PCA for feature selection?
negative_passages.docid: 152420
negative_passages.text: Robust PCA vs. robust Mahalanobis distance for outlier detection
negative_passages.docid: 25228
negative_passages.text: Interpreting 2D correspondence analysis plots
negative_passages.docid: 50148
negative_passages.text: Real-life examples of common distributions
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: 53419
negative_passages.text: Nice presentation of correlation matrix
negative_passages.docid: 154261
negative_passages.text: PCA when the dimensionality is greater than the number of samples
negative_passages.docid: 74282
negative_passages.text: Can I use PCA (or should I use regression) for testing the effect of multiple variables on one dependent variable?
negative_passages.docid: 90089
negative_passages.text: Why are PCA eigenvectors orthogonal and what is the relation to the PCA scores being uncorrelated?
negative_passages.docid: 126726
negative_passages.text: PCA, LDA, CCA, and PLS
negative_passages.docid: 51254
negative_passages.text: How to project a new vector onto the PC space using kernel PCA?
negative_passages.docid: 41608
negative_passages.text: Weighted principal components analysis
negative_passages.docid: 36609
negative_passages.text: Creating a single index from several principal components or factors retained from PCA/FA
negative_passages.docid: 101622
negative_passages.text: Choosing number of principal components to retain
negative_passages.docid: 16641
negative_passages.text: Strange results of varimax rotation of principal component analysis in Stata: rotated components are all zeros and ones