mlsanityData to 7 Oct 2026

Extremely Fast Decision Tree

arXiv 1802.08780 ↗First posted 24 Feb 2018cs.LG stat.MLcited by 42

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Abstract (arXiv)

We introduce a novel incremental decision tree learning algorithm, Hoeffding Anytime Tree, that is statistically more efficient than the current state-of-the-art, Hoeffding Tree. We demonstrate that an implementation of Hoeffding Anytime Tree---"Extremely Fast Decision Tree", a minor modification to the MOA implementation of Hoeffding Tree---obtains significantly superior prequential accuracy on most of the largest classification datasets from the UCI repository. Hoeffding Anytime Tree produces the asymptotic batch tree in the limit, is naturally resilient to concept drift, and can be used as a higher accuracy replacement for Hoeffding Tree in most scenarios, at a small additional computational cost.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). First posted on arXiv 24 Feb 2018.

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Citing papers per year: 2021: 5; 2022: 8; 2023: 4; 2024: 9; 2025: 9; 2026: 7.

42 papers.

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  1. 2021Deep Neural Networks and Tabular Data: A Surveycited by 489
  2. 2021A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streamscited by 28
  3. 2021PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streamscited by 17
  4. 2022IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspectivecited by 15
  5. 2021Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descentcited by 14
  6. 2025DFDT: Dynamic Fast Decision Tree for IoT Data Stream Mining on Edge Devicescited by 9
  7. 2022A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systemscited by 8
  8. 2025On-device edge learning for IoT data streams: a surveycited by 8
  9. 2025In-context Learning of Evolving Data Streams with Tabular Foundational Modelscited by 7
  10. 2022Dynamic Model Tree for Interpretable Data Stream Learningcited by 6
  11. 2025Bridging Streaming Continual Learning via In-Context Large Tabular Modelscited by 6
  12. 2022Learning from Data Streams: An Overview and Updatecited by 5
30 more
  1. 2025Online hierarchical partitioning of the output space in extreme multi-label data streamcited by 5
  2. 2022MABSplit: Faster Forest Training Using Multi-Armed Banditscited by 4
  3. 2023Des-q: a quantum algorithm to provably speedup retraining of decision treescited by 4
  4. 2022Green Accelerated Hoeffding Treecited by 3
  5. 2024Online Learning of Decision Trees with Thompson Samplingcited by 3
  6. 2024Hoeffding adaptive trees for multi-label classification on data streamscited by 3
  7. 2022Fully-Dynamic Decision Treescited by 2
  8. 2023Efficient Online Decision Tree Learning with Active Feature Acquisitioncited by 2
  9. 2023A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanismcited by 2
  10. 2024Employing Two-Dimensional Word Embedding for Difficult Tabular Data Stream Classificationcited by 2
  11. 2025Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networkscited by 2
  12. 2026Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensemblescited by 2
  13. 2021Shrub Ensembles for Online Classificationcited by 1
  14. 2023Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guaranteescited by 1
  15. 2024QC-Forest: a Classical-Quantum Algorithm to Provably Speedup Retraining of Random Forestcited by 1
  16. 2024Soft Hoeffding Tree: A Transparent and Differentiable Model on Data Streamscited by 1
  17. 2025Lift What You Can: Green Online Learning with Heterogeneous Ensemblescited by 1
  18. 2026Bounded Context Management for Tabular Foundation Models on Stream Learningcited by 1
  19. 2022Balancing Performance and Energy Consumption of Bagging Ensembles for the Classification of Data Streams in Edge Computingcited by 0
  20. 2024Simplifying Hyperparameter Tuning in Online Machine Learning -- The spotRiverGUIcited by 0
  21. 2024Constructing Decision Trees from Data Streamscited by 0
  22. 2024Online Nonparametric Supervised Learning for Massive Datacited by 0
  23. 2024Minimising changes to audit when updating decision treescited by 0
  24. 2025A Frank System for Co-Evolutionary Hybrid Decision-Makingcited by 0
  25. 2025CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detectioncited by 0
  26. 2026Approximating splits for decision trees quickly in sparse data streamscited by 0
  27. 2026On Imbalanced Regression with Hoeffding Treescited by 0
  28. 2026FastODT: A tree-based framework for efficient continual learningcited by 0
  29. 2026MIST: Reliable Streaming Decision Trees for Online Class-Incremental Learning via McDiarmid Boundcited by 0
  30. 2026Hoeffding adaptive splitting trees for data stream classification with concept drift and ensemble learningcited by 0