Welcome to the documentation of LCE!ΒΆ
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