Feature request: step_mca() or multiple correspondence analysis -- dimension reduction for categorical variables
Opened this issue · 2 comments
Similar to step_pca()
or step_umap()
where it may be useful for dimensional reduction, step_mca()
may seem useful for reducing dimensions for categorical predictors.
Thanks for this idea @exsell-jc! Do you typically use MASS::mca()
or something else for this kind of task?
Thanks for this idea @exsell-jc! Do you typically use
MASS::mca()
or something else for this kind of task?
Sure thing @juliasilge
Actually, I'm unsure if MASS
is better or FactoMineR
. I can't really seem to find any benchmarks or comparisons. MASS
does seem to be downloaded twice as often and more actively updated when looking at these two links:
https://www.rdocumentation.org/packages/FactoMineR/versions/2.4
https://www.rdocumentation.org/packages/MASS/versions/7.3-56