How to create separation of "sides"/signs in PCA / eigenvector "directionality of data" analysis?
Since PCA will only give eigenvectors that show the principal axes, but it does not specify, whether the data is skewed more towards the "plus side" of the eigenvectors or the "negative side".
What can I do to infer this type of thing?
So e.g. in this case separate between which arrow of PC1 is stronger than the other
https://medium.com/analytics-vidhya/pca-vs-t-sne-17bcd882bf3d