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Counterfactual Explanation
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Returns a contrastive argument that permits to achieve the desired class, e.g., “to obtain this loan, you need XXX of annual revenue instead of the current YYY”
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://gitlab.inria.fr/tguyet/vcnet/
공식 코드VCNet: A self-explaining model for realistic counterfactual generation
https://github.com/11301858/xaisuite
https://github.com/MartinPawel/ProbabilisticallyRobustRecourse
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
https://github.com/carla-recourse/CARLA
CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
https://github.com/ciselab/lampion
https://github.com/damiaanr/fact-ai
Explaining Groups of Points in Low-Dimensional Representations
https://github.com/elfrink1/FACT
Explaining Groups of Points in Low-Dimensional Representations
https://github.com/interpretml/DiCE
https://github.com/jpmorganchase/cf-shap-facct22
https://github.com/openxaiproject/pnpxai
Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
https://github.com/sobieskibj/rcsb
https://github.com/understanding-ml/COLA
Global Counterfactual Explanations: Investigations, Implementations and Improvements
https://github.com/yramon/ShapCounterfactual
Counterfactual Explanation Algorithms for Behavioral and Textual Data
https://github.com/yramon/edc
Counterfactual Explanation Algorithms for Behavioral and Textual Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.