incremental_decision_tree-CART-Random_Forest

Decision Tree Library

An implementation of incremental decision tree algorithms and ensemble methods for efficient machine learning on streaming data

incremental CART decision tree, based on the hoeffding tree i.e. very fast decision tree (VFDT), which is proposed in this paper "Mining High-Speed Data Streams" by Domingos & Hulten (2000). And a newly extended model "Extremely Fast Decision Tree" (EFDT) by Manapragada, Webb & Salehi (2018). Added new implementation of Random Forest

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28 forks
Language: Python
last commit: about 4 years ago
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