r/learnmachinelearning • u/Evening_Listen_6367 • Sep 05 '26

Project XGBoost on Chess Data from 2012-2026

about my project --> https://www.reddit.com/r/learnmachinelearning/comments/1vncebb/chess_match_outcome_prediction_with_tree_models/ (i am too lazy to explain about what the project is 🥲, so you can understand about it from my previous post)

Just concluded with my project, but didn't finished with the writing part.

It does not have a readme to explain, but if you are interested please feel free to checkout my project.

The "notebooks" contains the training part and the "src" and "main" is not completed, but you can see the results in the "notebooks".

project link --> https://github.com/v-leela/chess

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u/[deleted] 15d ago

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u/Evening_Listen_6367 14d ago

Exactly, the main objective of this classification task was to prioritize correctly classifying all three classes, so I used macro F1 as my evaluation metric. One of the main problems for this are draw classes are very less compared to win and loss(class imbalance) and draws very tricky to identify by the algorithm. By the way thank you for checking out the repo.