Our classifier outperforms CatBoost, XGBoost, LightGBM on 5 benchmark datasets

• linearboost-classifier

  2 101 7.7 Python

  LinearBoost Classifier is a rapid and accurate classification algorithm that builds upon a very fast, linear classifier.

  

The key to LinearBoost's enhanced performance lies in its approach at each estimator stage. Unlike decision trees used in GBDTs, which select features sequentially, LinearBoost utilizes a linear classifier as its building block, considering all available features simultaneously. This comprehensive feature integration allows for more robust decision-making processes at every step.

We believe LinearBoost can be a valuable tool for both academic research and real-world applications. Check out our results and code in our GitHub repo: https://github.com/LinearBoost/linearboost-classifier

We'd love to get your feedback and suggestions for further improvements!

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