Individualized help for at-risk students using model-agnostic and counterfactual explanations
Sign Up to like & getrecommendations! Published in 2021 at "Education and Information Technologies"
DOI: 10.1007/s10639-021-10661-6
Abstract: Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual… read more here.
Keywords: agnostic counterfactual; risk; risk students; model agnostic ... See more keywords
Model-agnostic Counterfactual Explanations in Credit Scoring
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DOI: 10.1109/access.2022.3177783
Abstract: The past decade has shown a surge in the use and application of machine learning and deep learning models across different domains. One such domain is the credit scoring domain, where applicants are scored to… read more here.
Keywords: counterfactual explanations; credit; credit scoring; explanations credit ... See more keywords
The Robustness of Counterfactual Explanations Over Time
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DOI: 10.1109/access.2022.3196917
Abstract: Counterfactual explanations are a prominent example of post-hoc interpretability methods in the explainable Artificial Intelligence (AI) research domain. Differently from other explanation methods, they offer the possibility to have recourse against unfavourable outcomes computed by… read more here.
Keywords: counterfactual explanations; time; machine learning; robustness counterfactual ... See more keywords
Factual and Counterfactual Explanations for Black Box Decision Making
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DOI: 10.1109/mis.2019.2957223
Abstract: The rise of sophisticated machine learning models has brought accurate but obscure decision systems, which hide their logic, thus undermining transparency, trust, and the adoption of artificial intelligence (AI) in socially sensitive and safety-critical contexts.… read more here.
Keywords: counterfactual explanations; black box; explanations black; factual counterfactual ... See more keywords
Factual and Counterfactual Explanations in Fuzzy Classification Trees
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DOI: 10.1109/tfuzz.2022.3179582
Abstract: Classification algorithms have recently acquired great popularity due to their efficiency to generate models capable of solving high complexity problems. Specifically, black box models are the ones that offer the best results, since they greatly… read more here.
Keywords: counterfactual explanations; factual explanation; factual counterfactual; explanations fuzzy ... See more keywords
A novel method to derive personalized minimum viable recommendations for type 2 diabetes prevention based on counterfactual explanations
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DOI: 10.1371/journal.pone.0272825
Abstract: Despite the growing availability of artificial intelligence models for predicting type 2 diabetes, there is still a lack of personalized approaches to quantify minimum viable changes in biomarkers that may help reduce the individual risk… read more here.
Keywords: counterfactual explanations; minimum viable; risk; based counterfactual ... See more keywords