Saved in:
| Main Authors: | de Oliveira, Filipe Ferreira, Rocha, Matheus Becali, Krohling, Renato A. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.19896 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Combining SHAP and Causal Analysis for Interpretable Fault Detection in Industrial Processes
by: Santos, Pedro Cortes dos, et al.
Published: (2025)
by: Santos, Pedro Cortes dos, et al.
Published: (2025)
Enhancing SHAP Explainability for Diagnostic and Prognostic ML Models in Alzheimer Disease
by: Guillén, Pablo, et al.
Published: (2026)
by: Guillén, Pablo, et al.
Published: (2026)
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
by: Li, Na, et al.
Published: (2025)
by: Li, Na, et al.
Published: (2025)
SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis
by: Hu, Yan, et al.
Published: (2025)
by: Hu, Yan, et al.
Published: (2025)
Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression
by: Kraev, Egor, et al.
Published: (2024)
by: Kraev, Egor, et al.
Published: (2024)
REFRESH: Responsible and Efficient Feature Reselection Guided by SHAP Values
by: Sharma, Shubham, et al.
Published: (2024)
by: Sharma, Shubham, et al.
Published: (2024)
Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection
by: Kelodjou, Gwladys, et al.
Published: (2023)
by: Kelodjou, Gwladys, et al.
Published: (2023)
Explainable time-series forecasting with sampling-free SHAP for Transformers
by: Hertel, Matthias, et al.
Published: (2025)
by: Hertel, Matthias, et al.
Published: (2025)
Physiologically Grounded Driver Behavior Classification: SHAP-Driven Elite Feature Selection and Hybrid Gradient Boosting for Multimodal Physiological Signals
by: Askari, Sahar, et al.
Published: (2026)
by: Askari, Sahar, et al.
Published: (2026)
Explainable AI for survival analysis: a median-SHAP approach
by: Ter-Minassian, Lucile, et al.
Published: (2024)
by: Ter-Minassian, Lucile, et al.
Published: (2024)
Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
by: Ng, Woon Yee, et al.
Published: (2025)
by: Ng, Woon Yee, et al.
Published: (2025)
SHAP-Guided Regularization in Machine Learning Models
by: Saadallah, Amal
Published: (2025)
by: Saadallah, Amal
Published: (2025)
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
by: Salih, Ahmed, et al.
Published: (2023)
by: Salih, Ahmed, et al.
Published: (2023)
SHAP-based Explanations are Sensitive to Feature Representation
by: Hwang, Hyunseung, et al.
Published: (2025)
by: Hwang, Hyunseung, et al.
Published: (2025)
From SHAP Scores to Feature Importance Scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
CQD-SHAP: Explainable Complex Query Answering via Shapley Values
by: Abbasi, Parsa, et al.
Published: (2025)
by: Abbasi, Parsa, et al.
Published: (2025)
Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
by: Kong, Lingxiao, et al.
Published: (2026)
by: Kong, Lingxiao, et al.
Published: (2026)
Breast Cancer Classification Using Gradient Boosting Algorithms Focusing on Reducing the False Negative and SHAP for Explainability
by: Pinheiro, João Manoel Herrera, et al.
Published: (2024)
by: Pinheiro, João Manoel Herrera, et al.
Published: (2024)
ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation
by: Dwiyanti, Latifa, et al.
Published: (2025)
by: Dwiyanti, Latifa, et al.
Published: (2025)
Lightweight Intrusion Detection in IoT via SHAP-Guided Feature Pruning and Knowledge-Distilled Kronecker Networks
by: Benaddi, Hafsa, et al.
Published: (2025)
by: Benaddi, Hafsa, et al.
Published: (2025)
Stroke Disease Classification Using Machine Learning with Feature Selection Techniques
by: Hasan, Mahade, et al.
Published: (2025)
by: Hasan, Mahade, et al.
Published: (2025)
The Distributional Uncertainty of the SHAP score in Explainable Machine Learning
by: Cifuentes, Santiago, et al.
Published: (2024)
by: Cifuentes, Santiago, et al.
Published: (2024)
A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
by: Hiraki, Kazuhiro, et al.
Published: (2026)
by: Hiraki, Kazuhiro, et al.
Published: (2026)
Explainable Threat Attribution for IoT Networks Using Conditional SHAP and Flow Behavior Modelling
by: Ozechi, Samuel, et al.
Published: (2026)
by: Ozechi, Samuel, et al.
Published: (2026)
Quadrature-TreeSHAP: Depth-Independent TreeSHAP and Shapley Interactions
by: Wettenstein, Ron, et al.
Published: (2026)
by: Wettenstein, Ron, et al.
Published: (2026)
Urinary Tract Infection Detection in Digital Remote Monitoring: Strategies for Managing Participant-Specific Prediction Complexity
by: Fan, Kexin, et al.
Published: (2025)
by: Fan, Kexin, et al.
Published: (2025)
SHAP-Based Supervised Clustering for Sample Classification and the Generalized Waterfall Plot
by: Lin, Justin, et al.
Published: (2025)
by: Lin, Justin, et al.
Published: (2025)
RoSHAP: A Distributional Framework and Robust Metric for Stable Feature Attribution
by: Xiang, Lanxin, et al.
Published: (2026)
by: Xiang, Lanxin, et al.
Published: (2026)
Beyond Accuracy: A Unified Random Matrix Theory Diagnostic Framework for Crash Classification Models
by: Shihab, Ibne Farabi, et al.
Published: (2026)
by: Shihab, Ibne Farabi, et al.
Published: (2026)
TabSHAP
by: Chaudhary, Aryan, et al.
Published: (2026)
by: Chaudhary, Aryan, et al.
Published: (2026)
Explainable Fact-checking through Question Answering
by: Yang, Jing, et al.
Published: (2021)
by: Yang, Jing, et al.
Published: (2021)
RankSHAP: Shapley Value Based Feature Attributions for Learning to Rank
by: Chowdhury, Tanya, et al.
Published: (2024)
by: Chowdhury, Tanya, et al.
Published: (2024)
Enhancing Classification Performance via Reinforcement Learning for Feature Selection
by: Jahed, Younes Ghazagh, et al.
Published: (2024)
by: Jahed, Younes Ghazagh, et al.
Published: (2024)
SHAP Distance: An Explainability-Aware Metric for Evaluating the Semantic Fidelity of Synthetic Tabular Data
by: Yu, Ke, et al.
Published: (2025)
by: Yu, Ke, et al.
Published: (2025)
Detecting Cybersecurity Threats by Integrating Explainable AI with SHAP Interpretability and Strategic Data Sampling
by: Srisumrith, Norrakith, et al.
Published: (2026)
by: Srisumrith, Norrakith, et al.
Published: (2026)
PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression
by: Fumagalli, Fabian, et al.
Published: (2026)
by: Fumagalli, Fabian, et al.
Published: (2026)
Interpretability-Guided Bi-objective Optimization: Aligning Accuracy and Explainability
by: Fouladi, Kasra, et al.
Published: (2026)
by: Fouladi, Kasra, et al.
Published: (2026)
The Rlign Algorithm for Enhanced Electrocardiogram Analysis through R-Peak Alignment for Explainable Classification and Clustering
by: Plagwitz, Lucas, et al.
Published: (2024)
by: Plagwitz, Lucas, et al.
Published: (2024)
Interaction Tensor SHAP
by: Hasegawa, Hiroki, et al.
Published: (2025)
by: Hasegawa, Hiroki, et al.
Published: (2025)
The Impact of Battery Cell Configuration on Electric Vehicle Performance: An XGBoost-Based Classification with SHAP Interpretability
by: Wishal, Santanam, et al.
Published: (2026)
by: Wishal, Santanam, et al.
Published: (2026)
Similar Items
-
Combining SHAP and Causal Analysis for Interpretable Fault Detection in Industrial Processes
by: Santos, Pedro Cortes dos, et al.
Published: (2025) -
Enhancing SHAP Explainability for Diagnostic and Prognostic ML Models in Alzheimer Disease
by: Guillén, Pablo, et al.
Published: (2026) -
SHAP-Guided Kernel Actor-Critic for Explainable Reinforcement Learning
by: Li, Na, et al.
Published: (2025) -
SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis
by: Hu, Yan, et al.
Published: (2025) -
Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression
by: Kraev, Egor, et al.
Published: (2024)