Hey everyone! Till now, I am having a great summer. Great thanks to my mentors Ryan and German for their continuous support and help. A huge thanks to the mlpack community too. Hoping my GSOCer (Is this even a valid word?🤔) friends are also having a great time too.
I have recently achieved the first big milestone of my project i.e. the DecisionTreeRegressor. #2905 is complete and under the review process. Hopefully, in the next week, we may finally get it merged. It's been three months since I have been working on that PR and now I am feeling very great and proud of myself that I am able to contribute such a nice method that almost every mlpack user will use. It would be awesome if more people could take a look at it and give their valuable feedback. NG Sai, I remember you earlier mentioned some changes and I told you that it was not the right time. I think now is the best time for those suggestions. :) Some of the highlights of the work done are:- 1. A separate class DecisionTreeRegressor for regression trees. 2. An efficient prefix sum binary split finding algorithm that runs in O(n). 3. With the above optimization, our DecisionTreeRegressor implementation is giving good competition to sklearn in terms of both performance and accuracy. 4. Improved memory consumption for the Tree object by removing the use of `arma::vec` from the splitInfo for regression. (There are some thoughts on doing some changes to try to improve the same for the existing Decision Tree Classifier. But this is gonna be a future endeavour.) Now, the next part is going to be even more exciting. The next milestone is the XGBoost Regressor. There are going to be some crazy optimizations involved in this one and It will be fun to implement it. The architecture and API have been finalised and from tomorrow onwards, I will begin working on it. Thanks, Rishabh Garg
_______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
