PCA documentation!
PCA is a python package to perform Principal Component Analysis and to create insightful plots. The core of PCA is build on sklearn functionality to find maximum compatibility when combining with other packages. But this pca package can do a lot more. Besides the regular Principal Components, it can also perform SparsePCA, TruncatedSVD, and provide you with the information that can be extracted from the components.
- Summary of Functionalities:
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.
Note
Your ❤️ is important to keep maintaining this package. You can support in various ways, have a look at the sponser page. Report bugs, issues and feature extensions at github page.
pip install pca
Contents
Background
Installation
Methods
Outlier detection
Plots
Examples