Principal component analysis

@article{Abdi2010PrincipalCA,
  title={Principal component analysis},
  author={Herv{\'e} Abdi and Lynne J. Williams},
  journal={Wiley Interdisciplinary Reviews: Computational Statistics},
  year={2010},
  volume={2}
}
  • H. Abdi, L. Williams
  • Published 1 July 2010
  • Mathematics
  • Wiley Interdisciplinary Reviews: Computational Statistics
Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter‐correlated quantitative dependent variables. Its goal is to extract the important information from the table, to represent it as a set of new orthogonal variables called principal components, and to display the pattern of similarity of the observations and of the variables as points in maps. The quality of the PCA model can be evaluated using cross… 
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