Counterfactual explanations for machine learning models on heterogeneous data
Counterfactual explanation aims to identify minimal and meaningful changes required in an input instance to produce a different prediction from a given model. Counterfactual explanations can assist users in comprehending the model's current prediction, detecting model unfairness, and providing...
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| 格式: | Thesis-Doctor of Philosophy |
| 語言: | English |
| 出版: |
Nanyang Technological University
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/169968 |
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| 機構: | Nanyang Technological University |
| 語言: | English |