perl module for principal component analysis (PCA)


Statistics::PCA provides functions for principal component analysis (PCA). PCA transforms higher-dimensional data consisting of a number of possibly correlated variables into a smaller number of uncorrelated variables termed principal components (PCs). The higher the ranking of the PCs the greater the amount of variability that the PC accounts for.

This PCA procedure involves the calculation of the eigenvalue decomposition from a data covariance matrix after mean centering the data.


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Install libstatistics-pca-perl