Results 11 to 20 of about 776,810 (287)
Counterfactual Shapley Additive Explanations [PDF]
2022 ACM Conference on Fairness Accountability and Transparency, 2022 Feature attributions are a common paradigm for model explanations due to their simplicity in assigning a single numeric score for each input feature to a model.
Long, Jason +3 more
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Measuring Model Understandability by means of Shapley Additive Explanations [PDF]
2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2022 In this work we link the understandability of machine learning models to the complexity of their SHapley Additive exPlanations (SHAP). Thanks to this reframing we introduce two novel metrics for understandability: SHAP Length and SHAP Interaction Length.
ALonso-Moral, JM, Mariotti, E, Gatt, A
core +7 more sources
Explanation of machine learning models using shapley additive explanation and application for real data in hospital [PDF]
Computer Methods and Programs in Biomedicine, 2022 When using machine learning techniques in decision-making processes, the interpretability of the models is important. In the present paper, we adopted the Shapley additive explanation (SHAP), which is based on fair profit allocation among many stakeholders depending on their contribution, for interpreting a gradient-boosting decision tree model using ...
Yasunobu Nohara +3 more
openaire +7 more sources
Bankruptcy prediction using machine learning and Shapley additive explanations
Review of Quantitative Finance and Accounting, 2023 International audienceRecently, ensemble-based machine learning models have been widely used and have demonstrated their efficiency in bankruptcy prediction.
Nguyen, Hoang Hiep +5 more
core +4 more sources
Journal of Imaging, 2022 Dengue is a viral disease that primarily affects tropical and subtropical regions and is especially prevalent in South-East Asia. This mosquito-borne disease sometimes triggers nationwide epidemics, which results in a large number of fatalities.
Shihab Uddin Chowdhury +5 more
doaj +3 more sources
Interpretable machine learning in damage detection using Shapley Additive Explanations [PDF]
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2021 In recent years, Machine Learning (ML) techniques have gained popularity in Structural Health Monitoring (SHM). These have been particularly used for damage detection in a wide range of engineering applications such as wind turbine blades.
Artur Movsessian +5 more
core +4 more sources
Shapley Additive Explanations for Knowledge Discovery via Surrogate Models [PDF]
AIAA SCITECH 2023 Forum, 2023 It is sometimes desirable to delve further into how the inputs affect the output in design optimization and uncertainty analysis. Surrogate models such as Gaussian Process Regression and support vector regression are useful for such tasks and can be ...
Morlier, Joseph +6 more
core +3 more sources
Scalable Computation of Shapley Additive Explanations
The growing field of explainable AI (XAI) develops methods that help better understand ML model predictions. While SHapley Additive exPlanations (SHAP) is a widely-used, model-agnostic method for explaining predictions, its use comes with a significant ...
Dionysio, Christina +2 more
core +3 more sources
, 2022 Shapley Additive Explanations for Text Classification and Sentiment Analysis of Internet Movie ...
Rung-Ching Chen (12272613) +2 more
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Exact Shapley values for local and model-true explanations of decision tree ensembles
Machine Learning with Applications, 2022 Additive feature explanations using Shapley values have become popular for providing transparency into the relative importance of each feature to an individual prediction of a machine learning model. While Shapley values provide a unique additive feature
Thomas W. Campbell +3 more
doaj +1 more source