Local Cascade Ensemble (LCE) is a high-performing, scalable and user-friendly machine learning method for the general tasks of Classification and Regression.
In particular, LCE:
- Enhances the prediction performance of Random Forest and XGBoost by combining their strengths and adopting a complementary diversification approach
- Supports parallel processing to ensure scalability
- Handles missing data by design
- Adopts scikit-learn API for the ease of use
- Adheres to scikit-learn conventions to allow interaction with scikit-learn pipelines and model selection tools
- Is released in open source and commercially usable - Apache 2.0 license
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.. toctree:: :maxdepth: 2 :hidden: :caption: Documentation api
.. toctree:: :maxdepth: 2 :hidden: :caption: Contribute contribute
.. toctree:: :maxdepth: 2 :hidden: :caption: Reference reference