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[Doc] Update list of winning solutions in data science competitions using XGBoost #6173
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@hcho3 Could you please assign this to me? I would like to work on this & will update you regarding the PR as soon as possible? |
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@divya661 Thanks for taking interest in this. Assigned. From what I understand, there's no limit on the number of participants, so many people can work on the same topic. Especially for this issue, we can submit different solutions from different sources but still count as contribution. |
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@hcho3 @trivialfis is this still open ? |
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@Wittty-Panda Yes, this issue is still open. Feel free to add more. |
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okay ,sir. I will do my best. |
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@hcho3 do i have to make another section for data science or just add them in machine learning one ? |
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@Wittty-Panda Just add them to the section titled |
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okay sir |
The demo directory shows a list of winning solutions for data science competitions that used XGBoost:
https://github.com/dmlc/xgboost/blob/master/demo/README.md#machine-learning-challenge-winning-solutions
The list hasn't been updated since October 2017. It would be great if we can update this list.
How to update the list.
https://www.kaggle.com/competitions is a great place to start. For each completed competition, look for the first, second, and third-place solutions. If they used XGBoost (even as part of ensemble), create a pull request to add them to https://github.com/dmlc/xgboost/blob/master/demo/README.md.
There are other data science competitions as well. For example, XGBoost was used in the first winning solution of ACM RecSys 2020 Challenge.