Background

pca is a python package to perform Principal Component Analysis and to examine the variance in-depth. The core of PCA is build on sklearn to find maximum compatibility when combining with other packages. But this package can do a lot more. Besides the regular Principal Components, it also integrates SparsePCA, TruncatedSVD, and provides the information that can be extracted from the components.

Functionalities of PCA are:

• Biplot to plot the loadings

• Determine the explained variance

• Extract the best performing features

• Scatter plot with the loadings

• Outlier detection using Hotelling T2 and/or SPE/Dmodx

• Removing unwantend (technical) bias from the data

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