Dear mlpack community, I'm writing to follow up on my GSoC project proposal for improving ensemble trees with XGBoost implementation. I submitted my proposal a few days ago and wanted to check if you'd had a chance to review it yet. My proposal aims to enhance the performance of ensemble trees in mlpack by implementing XGBoost, a machine-learning algorithm that uses decision trees as base learners. You can access the detailed project plan and timeline through this link: https://docs.google.com/document/d/1mQx5e7thE42zIlEPO2U5aUkk4sZfvDZxBWtTYgytrNY/edit?usp=sharing .
I would appreciate any feedback you may have on my proposal. Thank you for considering my application for the GSoC project. Best regards, Adarsh Santoria Github link: https://github.com/AdarshSantoria On Mon, Mar 20, 2023 at 12:53 AM Adarsh Santoria <adarshsanto...@gmail.com> wrote: > Dear mlpack community, > > My name is Adarsh Santoria, and I am a sophomore at IIT Mandi, India. I am > writing to submit my proposal for the GSoC project on improving ensemble > trees with XGBoost implementation. You can access the document through this > link: > https://docs.google.com/document/d/1mQx5e7thE42zIlEPO2U5aUkk4sZfvDZxBWtTYgytrNY/edit?usp=sharing, > which outlines my project plan and timeline in detail. XGBoost is a machine > learning algorithm that uses decision trees as base learners, known for its > high accuracy, interpretability, scalability, feature importance, and > robustness to noisy or incomplete data. Implementing XGBoost in mlpack is a > necessary step towards enhancing the performance of ensemble trees, making > it an important contribution to the mlpack community. > > In summary, my proposal includes the following: > ● Implementing Random Forest Regressor method and adding tests > ● Parallelizing decision tree, random forest and xgboost with OpenMP > ● Adding bindings for the decision tree, random forest and xgboost > ● Adding the XGBoost Classifier and Regressor along with some split > methods and loss functions. > ● Adding tutorials and sample code snippets > > I believe that with my skills and experience, I can make significant > contributions to mlpack and enhance the performance of ensemble trees with > XGBoost implementation. > Thank you for considering my proposal for the GSoC project. > > Best regards, > Adarsh Santoria > Github link: https://github.com/AdarshSantoria >
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