Principal components analysis.

  title={Principal components analysis.},
  author={Detlef Groth and Stefanie Hartmann and Sebastian Klie and Joachim Selbig},
  journal={Methods in molecular biology},
Principal components analysis (PCA) is a standard tool in multivariate data analysis to reduce the number of dimensions, while retaining as much as possible of the data's variation. Instead of investigating thousands of original variables, the first few components containing the majority of the data's variation are explored. The visualization and… CONTINUE READING