I'm doing multi-class classification on the Abalone dataset by divided the abalone into age groups young, adult and old.
While doing so, I found that the columns for the abalone size and weights were highly correlated. I'm also using the sex categories via one-hot encoding.
The dataset info also mentioned that "Data set samples are highly overlapped. Further information is required to separate completely using affine combinations."
What are the implications of this high correlations, and how do I perform my feature engineering knowing this?