7 ms·
Great work! This looks to have come a long ways since I last looked at it! Do you have benchmarks? I've been working on a similar project just for decision tr
by micro_cam 12y ago
Great work! This looks to have come a long ways since I last looked at it!
Do you have benchmarks?
I've been working on a similar project just for decision tree learning [1]. I've been able to get performance just about equal to scikit learn which is the current fastest open implementation [2]. I can beat it in some cases with lots of binary features.
I'll see about including a compatibility layer for integration with golearn. I'm actually also currently squatting the golearn github org but will pass it off if you are interested.
[1] https://github.com/ryanbressler/CloudForest https://github.com/ryanbressler/CloudForest
[2] based on benchmarks here http://orbi.ulg.ac.be/handle/2268/170309 http://orbi.ulg.ac.be/handle/2268/170309
[3] https://github.com/golearn https://github.com/golearn
- struct 12y ago(Disclaimer: I'm one of the authors). For decision trees, the only thing that's available at the moment is a half-baked ID3 algorithm, but I've been looking at CloudForest and it's a very impressive piece of work. Performance isn't very good yet: this is due to some data representation decisions, but it now supports grouping attributes which will allow us to optimise to acceptable performance levels (I have a prototype KNN version which achieved similar performance levels to this guy's Rust[1] implementation). [1] http://huonw.github.io/2014/06/10/knn-rust.html http://huonw.github.io/2014/06/10/knn-rust.html