[P] Dimensionality Reduction Methods for a dataset with continuous and binary features?
I was told to use PCA from my postdoc supervisor, but I realized it is best for continuous features. I’ve looked into splitting my data to do a PCA with continuous features and MCA for binary. My postdoc supervisor said he combined the results – I was wondering how? A PCA returns PC1 and PC2 with coordinates (length = dataframe size). My MCA returns dim1 and dim2 but with 24 coordinates for the binary data. I’m not sure how to proceed?
But if there is another method that someone could recommend would be much appreciated! I am using R currently. But I can use Python too.