LocalCascadeEnsemble/LCE
Random Forest or XGBoost? It is Time to Explore LCE
This project offers a high-performing and scalable machine learning method for predicting outcomes and classifying data. It takes your raw datasets, even with missing information, and delivers enhanced prediction results for general classification and regression tasks. Data scientists, machine learning engineers, and researchers can use this to improve their existing predictive models.
No commits in the last 6 months.
Use this if you need to build or improve predictive models for classification or regression and want better accuracy and scalability than traditional Random Forest or XGBoost.
Not ideal if you are looking for a simple, out-of-the-box solution without any programming, or if your primary need is interpretable models over raw predictive performance.
Stars
70
Forks
11
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 15, 2023
Commits (30d)
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