contrastive

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Adding greater visibility of plots, as well as scree plots for greater comparison ability

1

Hello, I added some additional features to this wonderful method you have. Included are x and y-axis labels that represent the %variance explained by each principal component, as well as...

patjiang

abidlabs

Hi, Thanks for the beautiful algorithm! I wonder if cPCA can do `pca.inverse_transform()` like in the PCA in scikit-learn. Thank you!

hliu56

Hi How do i get Explainable-variance of each principal component?Because I want to determine how many principal component numbers to set is reliable.

eliauk07yz