Hi Racket Users,

The last few days I've been working on implementing decision trees in Racket 
and I've been following the following guide: 

Now I have the following code: https://github.com/ZelphirKaltstahl/racket-ml

I also wrote some tests, I think for every procedure so far.

However, my implementation seems very very slow. It seems each iteration of 
`iter-features` takes way too much time.

I've tried to stick to the guide and sometimes "outsourced" some procedure.

I started out with using vectors, as I thought I might gain better performance 
than from lists. In the code I introduced an abstraction layer, which provides 
things like `data-length`, so that I could in theory change the representation 
of data and only change those accessors/getters. In the test cases I sometimes 
did not use the abstraction though.

So far I am not having much side effects in the code and I'd like to avoid them 
and unsafe operations.

A small `TEST-DATA` set is in the code and another data set I downloaded from 
the data set repositories. When running with `TEST-DATA` to calculate the best 
split, it only takes a few milliseconds, while it takes minutes with the other 

How can I make my code more efficient, without changing the basic logic of it?
Should I not use vectors (what else?)?
Would I gain anything from using typed Racket or flonums?

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