mlsanityData to 7 Oct 2026

FARF: A Fair and Adaptive Random Forests Classifier

arXiv 2108.07403 ↗First posted 17 Aug 2021cs.LG cs.AIcited by 37

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Abstract (arXiv)

As Artificial Intelligence (AI) is used in more applications, the need to consider and mitigate biases from the learned models has followed. Most works in developing fair learning algorithms focus on the offline setting. However, in many real-world applications data comes in an online fashion and needs to be processed on the fly. Moreover, in practical application, there is a trade-off between accuracy and fairness that needs to be accounted for, but current methods often have multiple hyperparameters with non-trivial interaction to achieve fairness. In this paper, we propose a flexible ensemble algorithm for fair decision-making in the more challenging context of evolving online settings. This algorithm, called FARF (Fair and Adaptive Random Forests), is based on using online component classifiers and updating them according to the current distribution, that also accounts for fairness and a single hyperparameters that alters fairness-accuracy balance. Experiments on real-world discriminated data streams demonstrate the utility of FARF.

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). Builds on 18 of its 49 references that are in the map. First posted on arXiv 17 Aug 2021.

Builds on

18 of 49 references.

References · 18

  1. 2016Equality of Opportunity in Supervised Learningcited by 2,000
  2. 2016Inherent Trade-Offs in the Fair Determination of Risk Scorescited by 582
  3. 2017Fairness in Machine Learning: Lessons from Political Philosophycited by 148
  4. 2016A Confidence-Based Approach for Balancing Fairness and Accuracycited by 73
  5. 2019Putting Fairness Principles into Practice: Challenges, Metrics, and Improvementscited by 70
  6. 2019FAHT: An Adaptive Fairness-aware Decision Tree Classifiercited by 63
  7. 2019Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learningcited by 57
  8. 2020FAE: A Fairness-Aware Ensemble Frameworkcited by 34
  9. 2020Disentangled Dynamic Graph Deep Generationcited by 27
  10. 2018Bayesian Modeling of Intersectional Fairness: The Variance of Biascited by 23
  11. 2018A Deterministic Self-Organizing Map Approach and its Application on Satellite Data based Cloud Type Classificationcited by 22
  12. 2015A survey on measuring indirect discrimination in machine learningcited by 15
6 more
  1. 2019Fairness-enhancing interventions in stream classificationcited by 15
  2. 2020Using Machine Learning to Automate Mammogram Images Analysiscited by 15
  3. 2021LSTM Based Sentiment Analysis for Cryptocurrency Predictioncited by 14
  4. 2021Cognitive Visual Commonsense Reasoning Using Dynamic Working Memorycited by 14
  5. 2020A Data-driven Human Responsibility Management Systemcited by 8
  6. 2021Responsibility Management through Responsibility Networkscited by 3

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Cited by year

Citing papers per year: 2021: 4; 2022: 12; 2023: 8; 2024: 9; 2025: 4.

37 papers.

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  1. 2021A survey on datasets for fairness-aware machine learningcited by 157
  2. 2022Bias Mitigation for Machine Learning Classifiers: A Comprehensive Surveycited by 125
  3. 2024History, Development, and Principles of Large Language Models-An Introductory Surveycited by 30
  4. 2022Longitudinal Fairness with Censorshipcited by 21
  5. 2022Transferring Fairness under Distribution Shifts via Fair Consistency Regularizationcited by 21
  6. 2022Fairness Amidst Non-IID Graph Data: A Literature Reviewcited by 20
  7. 2024FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applicationscited by 15
  8. 2023Towards Fair Machine Learning Software: Understanding and Addressing Model Bias Through Counterfactual Thinkingcited by 14
  9. 2023Preventing Discriminatory Decision-making in Evolving Data Streamscited by 12
  10. 2022How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shiftscited by 11
  11. 2023Individual Fairness under Uncertaintycited by 11
  12. 2024Fairness Definitions in Language Models Explainedcited by 10
25 more
  1. 2021Fair Tree Classifier using Strong Demographic Paritycited by 9
  2. 2022Incremental Mining of Frequent Serial Episodes Considering Multiple Occurrencescited by 7
  3. 2023Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Ratecited by 6
  4. 2021Efficient Algorithms For Fair Clustering with a New Fairness Notioncited by 5
  5. 2022Sustaining Fairness via Incremental Learningcited by 5
  6. 2025Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applicationscited by 5
  7. 2022FEAMOE: Fair, Explainable and Adaptive Mixture of Expertscited by 4
  8. 2023Improving Fairness with Ensemble Combination: Margin-Dependent Boundscited by 3
  9. 2025AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Modelscited by 3
  10. 2025Towards Transparent AI: A Survey on Explainable Language Modelscited by 3
  11. 2022On the Robustness of Random Forest Against Untargeted Data Poisoning: An Ensemble-Based Approachcited by 2
  12. 2022A Survey on Preserving Fairness Guarantees in Changing Environmentscited by 2
  13. 2023Fairness under Covariate Shift: Improving Fairness-Accuracy tradeoff with few Unlabeled Test Samplescited by 2
  14. 2024Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learningcited by 2
  15. 2021A Generic Knowledge Based Medical Diagnosis Expert Systemcited by 1
  16. 2023The Internet of Responsibilities-Connecting Human Responsibilities using Big Data and Blockchaincited by 1
  17. 2024Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AIcited by 1
  18. 2024Fair Mixed Effects Support Vector Machinecited by 1
  19. 2025Fairness-Aware Graph Representation Learning with Limited Demographic Informationcited by 1
  20. 2022Improving Specificity in Mammography Using Cross-correlation between Wavelet and Fourier Transformcited by 0
  21. 2022Attention Mechanism based Cognition-level Scene Understandingcited by 0
  22. 2023Continuous Management of Machine Learning-Based Application Behaviorcited by 0
  23. 2024Fair Generalized Linear Mixed Modelscited by 0
  24. 2024Leveraging Large Language Models through Natural Language Processing to provide interpretable Machine Learning predictions of mental deterioration in real timecited by 0
  25. 2024TowerDebias: A Novel Unfairness Removal Method Based on the Tower Propertycited by 0