Already fixed that `class-labels` issue, thanks, it was a quick fix today
morning. I already tested it with that change and it was way faster.
I thought about going for binary classification only while programming, but I
think I managed to keep it generic for multiple classes at least in most of the
code.
Maybe that is not necessary, because every n classes classification problem can
be expressed with n binary classifications ("in a class or in one of the
others", for each of the classes).
I think however not assuming 2 classes does not impact performance in this case.
If there are not only binary splits, but three parts split for example, the
algorithm becomes less efficient.
The reason is, that for each split value, one would have to check again all the
other split values of a feature and that would be O(n^2), I believe, instead of
O(n). So maybe not assuming binary splits just makes things harder on myself,
because no one is going to do three part splits or even more.
Thanks for your suggestions.
@Daniel Prager:
Thanks for posting that code, I might relate to it when getting there. Seems
concise. Maybe you could put it in a repository, so that other people are more
likely to find your code.
In general I think available libraries are important for creating attraction to
a programming language. For example I like Python's machine learning and data
munging libraries and this is one reason why I frequently use them. It would be
great to have something equally great in Racket, even if experienced Racket
programmers can code something up in a day or two.
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