Hello Developers, This is Aman Pratik. I am currently pursuing my B.Tech from Indian Institute of Technology, Varanasi. After doing some research I have found some material on Decision Trees and Parallelization. Hence, I propose my first draft for the project "Parallel Decision Tree Building" for GSoC 2017.
Proposal : First Draft <https://github.com/amanp10/scikit-learn/wiki/GSoC-2017-:-Parallel-Decision-Tree-Building> Why me? I have been working in Python for the past 2 years and have good idea about Machine Learning algorithms. I am quite familiar with scikit-learn both as a user and a developer. These are the issues/PRs I have worked/working on for the past few months. [MRG+1] Issue#5803 : Regression Test added #8112 <https://github.com/scikit-learn/scikit-learn/pull/8112> [MRG] Issue#6673:Make a wrapper around functions that score an individual feature #8038 <https://github.com/scikit-learn/scikit-learn/pull/8038> [MRG] Issue #7987: Embarrassingly parallel "n_restarts_optimizer" in GaussianProcessRegressor #7997 <https://github.com/scikit-learn/scikit-learn/pull/7997> My GitHub Profile: amanp10 <https://www.github.com/amanp10> I have worked with parallelization in one of my PR, so I am not new to it. I have used cython a couple of times, though as a beginner. I have not used Decision Tree much but I am familiar with the theory and algorithm. Also, I am familiar with Benchmark tests, Unit tests and other technical knowledge I would require for this project. Meanwhile, I have started my study for the subject and gaining experience with Cython. I am looking forward to guidance from the potential mentors or anyone willing to help. Thank You
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