Cross-validation methods in principal component analysis: A comparison
- Authors
- Giancarlo Diana and Chiara Tommasi
- Published
- 2002
- DOI
- 10.1007/BF02511446
- Citation
- Diana and Tommasi: "Cross-validation methods in principal component analysis: A comparison", Statistical Methods and Applications, 11, 71-82, 2002.
- Abstract
- In principal component analysis (PCA), it is crucial to know how many principal components (PCs) should be retained in order to account for most of the data variability. A class of “objective” rules for finding this quantity is the class of cross-validation (CV) methods. In this work we compare three CV techniques showing how the performance of these methods depends on the covariance matrix structure. Finally we propose a rule for the choice of the “best” CV method and give an application to real data.
- Tags
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