Understanding Prediction Discrepancies in Machine Learning Classifiers
Fuente:
arXiv
Saved in:
| Main Authors: | Renard, Xavier, Laugel, Thibault, Detyniecki, Marcin |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Post-processing fairness with minimal changes
by: Di Gennaro, Federico, et al.
Published: (2024)
by: Di Gennaro, Federico, et al.
Published: (2024)
SAKE: Steering Activations for Knowledge Editing
by: Scialanga, Marco, et al.
Published: (2025)
by: Scialanga, Marco, et al.
Published: (2025)
ACT: Agentic Classification Tree
by: Grari, Vincent, et al.
Published: (2025)
by: Grari, Vincent, et al.
Published: (2025)
Why do explanations fail? A typology and discussion on failures in XAI
by: Bove, Clara, et al.
Published: (2024)
by: Bove, Clara, et al.
Published: (2024)
Metric assessment protocol in the context of answer fluctuation on MCQ tasks
by: Goliakova, Ekaterina, et al.
Published: (2025)
by: Goliakova, Ekaterina, et al.
Published: (2025)
Controlled Model Debiasing through Minimal and Interpretable Updates
by: Di Gennaro, Federico, et al.
Published: (2025)
by: Di Gennaro, Federico, et al.
Published: (2025)
OptiGrad: A Fair and more Efficient Price Elasticity Optimization via a Gradient Based Learning
by: Grari, Vincent, et al.
Published: (2024)
by: Grari, Vincent, et al.
Published: (2024)
When mitigating bias is unfair: multiplicity and arbitrariness in algorithmic group fairness
by: Krco, Natasa, et al.
Published: (2023)
by: Krco, Natasa, et al.
Published: (2023)
Agentic Adversarial QA for Improving Domain-Specific LLMs
by: Grari, Vincent, et al.
Published: (2026)
by: Grari, Vincent, et al.
Published: (2026)
Predicting Diabetes Using Machine Learning: A Comparative Study of Classifiers
by: Hasan, Mahade, et al.
Published: (2025)
by: Hasan, Mahade, et al.
Published: (2025)
Understanding Gradient Boosting Classifier: Training, Prediction, and the Role of $γ_j$
by: Chen, Hung-Hsuan
Published: (2024)
by: Chen, Hung-Hsuan
Published: (2024)
Dynamic Interpretability for Model Comparison via Decision Rules
by: Rida, Adam, et al.
Published: (2023)
by: Rida, Adam, et al.
Published: (2023)
Hierarchical Scoring for Machine Learning Classifier Error Impact Evaluation
by: Lanus, Erin, et al.
Published: (2025)
by: Lanus, Erin, et al.
Published: (2025)
Alignment Reduces Expressed but Not Encoded Gender Bias: A Unified Framework and Study
by: Bouchouchi, Nour, et al.
Published: (2026)
by: Bouchouchi, Nour, et al.
Published: (2026)
Classifying Dental Care Providers Through Machine Learning with Features Ranking
by: Al-Batah, Mohammad Subhi, et al.
Published: (2025)
by: Al-Batah, Mohammad Subhi, et al.
Published: (2025)
Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers
by: Siedel, Georg, et al.
Published: (2022)
by: Siedel, Georg, et al.
Published: (2022)
Machine Learning for Pattern Detection in Printhead Nozzle Logging
by: Prianikov, Nikola, et al.
Published: (2025)
by: Prianikov, Nikola, et al.
Published: (2025)
Bridging Philosophy and Machine Learning: A Structuralist Framework for Classifying Neural Network Representations
by: Culcu, Yildiz
Published: (2025)
by: Culcu, Yildiz
Published: (2025)
A Comparative Study on Machine Learning Models to Classify Diseases Based on Patient Behaviour and Habits
by: Musaaed, Elham, et al.
Published: (2024)
by: Musaaed, Elham, et al.
Published: (2024)
Coordinate Matrix Machine: A Human-level Concept Learning to Classify Very Similar Documents
by: Sadri, Amin, et al.
Published: (2025)
by: Sadri, Amin, et al.
Published: (2025)
Distribution-Based Feature Attribution for Explaining the Predictions of Any Classifier
by: Li, Xinpeng, et al.
Published: (2025)
by: Li, Xinpeng, et al.
Published: (2025)
Conformal Prediction of Classifiers with Many Classes based on Noisy Labels
by: Penso, Coby, et al.
Published: (2025)
by: Penso, Coby, et al.
Published: (2025)
Predicting Tennis Serve directions with Machine Learning
by: Zhu, Ying, et al.
Published: (2026)
by: Zhu, Ying, et al.
Published: (2026)
Explainable Machine Learning for ICU Readmission Prediction
by: de Sá, Alex G. C., et al.
Published: (2023)
by: de Sá, Alex G. C., et al.
Published: (2023)
Learning Dynamic Representations via An Optimally-Weighted Maximum Mean Discrepancy Optimization Framework for Continual Learning
by: Huang, KaiHui, et al.
Published: (2025)
by: Huang, KaiHui, et al.
Published: (2025)
HistoKernel: Whole Slide Image Level Maximum Mean Discrepancy Kernels for Pan-Cancer Predictive Modelling
by: Keller, Piotr, et al.
Published: (2024)
by: Keller, Piotr, et al.
Published: (2024)
Bias Detection via Maximum Subgroup Discrepancy
by: Němeček, Jiří, et al.
Published: (2025)
by: Němeček, Jiří, et al.
Published: (2025)
Discrepancy-Aware Graph Mask Auto-Encoder
by: Zheng, Ziyu, et al.
Published: (2025)
by: Zheng, Ziyu, et al.
Published: (2025)
Online Drift Detection with Maximum Concept Discrepancy
by: Wan, Ke, et al.
Published: (2024)
by: Wan, Ke, et al.
Published: (2024)
Latenrgy: Model Agnostic Latency and Energy Consumption Prediction for Binary Classifiers
by: Pittman, Jason M.
Published: (2024)
by: Pittman, Jason M.
Published: (2024)
Fixed Random Classifier Rearrangement for Continual Learning
by: Huang, Shengyang, et al.
Published: (2024)
by: Huang, Shengyang, et al.
Published: (2024)
Bank Loan Prediction Using Machine Learning Techniques
by: Haque, F M Ahosanul, et al.
Published: (2024)
by: Haque, F M Ahosanul, et al.
Published: (2024)
Diabetes Prediction and Management Using Machine Learning Approaches
by: Alzboon, Mowafaq Salem, et al.
Published: (2025)
by: Alzboon, Mowafaq Salem, et al.
Published: (2025)
Automated Machine Learning for Remaining Useful Life Predictions
by: Zöller, Marc-André, et al.
Published: (2023)
by: Zöller, Marc-André, et al.
Published: (2023)
Federated Unlearning in the Wild: Rethinking Fairness and Data Discrepancy
by: Huang, ZiHeng, et al.
Published: (2025)
by: Huang, ZiHeng, et al.
Published: (2025)
Machine Learning for Climate Policy: Understanding Policy Progression in the European Green Deal
by: West, Patricia, et al.
Published: (2025)
by: West, Patricia, et al.
Published: (2025)
Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm
by: Renard, Titouan, et al.
Published: (2024)
by: Renard, Titouan, et al.
Published: (2024)
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
by: Szatkowski, Filip, et al.
Published: (2024)
by: Szatkowski, Filip, et al.
Published: (2024)
Stroke Prediction using Clinical and Social Features in Machine Learning
by: Chadha, Aidan
Published: (2024)
by: Chadha, Aidan
Published: (2024)
Predicting BWR Criticality with Data-Driven Machine Learning Model
by: Oktavian, Muhammad Rizki, et al.
Published: (2024)
by: Oktavian, Muhammad Rizki, et al.
Published: (2024)
Similar Items
-
Post-processing fairness with minimal changes
by: Di Gennaro, Federico, et al.
Published: (2024) -
SAKE: Steering Activations for Knowledge Editing
by: Scialanga, Marco, et al.
Published: (2025) -
ACT: Agentic Classification Tree
by: Grari, Vincent, et al.
Published: (2025) -
Why do explanations fail? A typology and discussion on failures in XAI
by: Bove, Clara, et al.
Published: (2024) -
Metric assessment protocol in the context of answer fluctuation on MCQ tasks
by: Goliakova, Ekaterina, et al.
Published: (2025)