I have a problem figuring out how to visualize two simple quantities using R. I want to compare their size by visualizing two proportional spatial figures next to each other and the size proportional to their volume, height or whatever. E.g. I have two numbers 45 and 15, after my code execution I would get two spatial figures, but first is three times bigger. 
https://visual.ly/blog/45-ways-to-communicate-two-quantities/ <- I want to do something like in this article example no.26 "Volumes". 
Figures could be like cone, cube or 3d pie. Is is possible to realize that using ggplot2 or any other package?
Correlated features in general don't improve models (although it depends on the specifics of the problem like the number of variables and the degree of correlation), but they affect specific models in different ways and to varying extents:


For linear models (e.g., linear regression or logistic regression), multicolinearity can yield solutions that are wildly varying and possibly numerically unstable.
Random forests can be good at detecting interactions between different features, but highly correlated features can mask these interactions.


More generally, this can be viewed as a special case of Occam's razor. A simpler model is preferable, and, in some sense, a model with fewer features is simpler. The concept of minimum description length makes this more precise.
