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| courses:xai:p2_2024 [2025/01/13 09:13] – [Xai and GenAI] admin | courses:xai:p2_2024 [2026/01/19 07:23] (current) – [Alpha Evolve] admin | ||
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| - | ===== Shap on OPTUNA | + | ===== ACFXon |
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| - | The goal is to run hyperparameter optimization algorithm such as optuna, collect results from it and use SHAP to try to explain the impact of different hyperparameters on the quality of the optimization process | + | The goal is to run hyperparameter optimization algorithm such as optuna, collect results from it and use [[https:// |
| ===== PPCF Counterfactual explainer evaluation | ===== PPCF Counterfactual explainer evaluation | ||
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| + | ===== Alpha Evolve ===== | ||
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| + | Try to setup and raun exmaple from AlphaEvolve public implementation: | ||
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| + | ===== Run and compare different XAI methos on anomaly detection task ===== | ||
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| + | Focus on rule-based explainers, but also SAHP and LIME: calculate output for anomaly detection task (e.g.: https:// | ||