mlsanityData to 14 Oct 2026

Scikit-Multiflow: A Multi-output Streaming Framework

arXiv 1807.04662 ↗First posted 12 Jul 2018cs.LG stat.MLcited by 70

Not on the map. Why?

Abstract (arXiv)

Scikit-multiflow is a multi-output/multi-label and stream data mining framework for the Python programming language. Conceived to serve as a platform to encourage democratization of stream learning research, it provides multiple state of the art methods for stream learning, stream generators and evaluators. scikit-multiflow builds upon popular open source frameworks including scikit-learn, MOA and MEKA. Development follows the FOSS principles and quality is enforced by complying with PEP8 guidelines and using continuous integration and automatic testing. The source code is publicly available at https://github.com/scikit-multiflow/scikit-multiflow.

Key facts. Cited by 70 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Jul 2018.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 18; 2022: 17; 2023: 6; 2024: 16; 2025: 10; 2026: 3.

70 papers.

Sort:

By area:

  1. 2022A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental frameworkcited by 39
  2. 2021A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streamscited by 28
  3. 2024Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Datacited by 25
  4. 2021Detecting Concept Drift With Neural Network Model Uncertaintycited by 22
  5. 2023Model Based Explanations of Concept Driftcited by 21
  6. 2021STUDD: A Student-Teacher Method for Unsupervised Concept Drift Detectioncited by 19
  7. 2021PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streamscited by 17
  8. 2023Online Boosting Adaptive Learning under Concept Drift for Multistream Classificationcited by 17
  9. 2022IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspectivecited by 16
  10. 2024A Survey on Failure Analysis and Fault Injection in AI Systemscited by 10
  11. 2021A Survey on Spatio-temporal Data Analytics Systemscited by 9
  12. 2021Active Weighted Aging Ensemble for Drifted Data Stream Classificationcited by 8
38 more
  1. 2022Suitability of Different Metric Choices for Concept Drift Detectioncited by 8
  2. 2022Change Detection for Local Explainability in Evolving Data Streamscited by 8
  3. 2025When to retrain a machine learning modelcited by 8
  4. 2023Cost-Effective Retraining of Machine Learning Modelscited by 7
  5. 2023One or Two Things We know about Concept Drift -- A Survey on Monitoring Evolving Environmentscited by 7
  6. 2022Dynamic Model Tree for Interpretable Data Stream Learningcited by 6
  7. 2022Fast & Furious: Modelling Malware Detection as Evolving Data Streamscited by 6
  8. 2021MRCpy: A Library for Minimax Risk Classifierscited by 5
  9. 2021ACDC: Online Unsupervised Cross-Domain Adaptationcited by 4
  10. 2022Autoregressive based Drift Detection Methodcited by 4
  11. 2022Standardized Evaluation of Machine Learning Methods for Evolving Data Streamscited by 4
  12. 2023Adaptive Bernstein Change Detector for High-Dimensional Data Streamscited by 4
  13. 2021Automatic Learning to Detect Concept Driftcited by 3
  14. 2021On-the-Fly Ensemble Pruning in Evolving Data Streamscited by 3
  15. 2021A Broad Ensemble Learning System for Drifting Stream Classificationcited by 3
  16. 2022Unfolding AIS transmission behavior for vessel movement modeling on noisy data leveraging machine learningcited by 3
  17. 2023DynED: Dynamic Ensemble Diversification in Data Stream Classificationcited by 3
  18. 2024Identifying Predictions That Influence the Future: Detecting Performative Concept Drift in Data Streamscited by 3
  19. 2025IncA-DES: An incremental and adaptive dynamic ensemble selection approach using online K-d tree neighborhood search for data streams with concept driftcited by 3
  20. 2021Automated Machine Learning Techniques for Data Streamscited by 2
  21. 2024Unsupervised Concept Drift Detection based on Parallel Activations of Neural Networkcited by 2
  22. 2024Employing Two-Dimensional Word Embedding for Difficult Tabular Data Stream Classificationcited by 2
  23. 2024DriftGAN: Using historical data for Unsupervised Recurring Drift Detectioncited by 2
  24. 2024A Probabilistic Framework for Adapting to Changing and Recurring Concepts in Data Streamscited by 2
  25. 2025CapyMOA: Efficient Machine Learning for Data Streams and Online Continual Learning in Pythoncited by 2
  26. 2021Domain Specific Concept Drift Detectors for Predicting Financial Time Seriescited by 1
  27. 2021Incremental Learning Techniques for Online Human Activity Recognitioncited by 1
  28. 2021Differentially Private Ensemble Classifiers for Data Streamscited by 1
  29. 2022Frouros: A Python library for drift detection in machine learning systemscited by 1
  30. 2024On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Datacited by 1
  31. 2024Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messagescited by 1
  32. 2024A Self-Organizing Clustering System for Unsupervised Distribution Shift Detectioncited by 1
  33. 2024Structuring the Processing Frameworks for Data Stream Evaluation and Applicationcited by 1
  34. 2025Histogram Approaches for Imbalanced Data Streams Regressioncited by 1
  35. 2021Online Binary Models are Promising for Distinguishing Temporally Consistent Computer Usage Profilescited by 0
  36. 2021Sketches for Time-Dependent Machine Learningcited by 0
  37. 2021Online Feature Selection for Efficient Learning in Networked Systemscited by 0
  38. 2022Implicit Concept Drift Detection for Multi-label Data Streamscited by 0

50 most cited of 70 All 70 (JSON)