Machine learning in Clojure with clj-boost

Hi everyone! I’m really happy to let you know that I made Clojure wrappers for XGBoost:

Any comment is very helpful: issues, ideas, usage examples and so on. At the moment there is only the main README explaining how to use clj-boost and this (uncommented) demo.

As soon as possible I’ll write some tutorials and some use cases examples, but in the mean time I would like to know what you think about it and if you start using it (even for personal projects) how it feels.

I already have some sort of a roadmap:

  • Make some tutorials and posts about clj-boost usage
  • Add a method to generate config programmatically (atom?)
  • Add a way to perform grid search over parameters
  • Some facilities (like accuracy, confusion matrix, etc)???

But it’s difficult to know which way to go if I don’t get some kind of feedback (even critical feedback is ok)


I just released a new version with improved docs and a thorough tutorial on how to use clj-boost


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