Overcoming Confounding Bias in Causal Discovery Using Minimum Redundancy and Maximum Relevancy Constraint
Causal discovery is the process of modeling cause and effect relationships among features. Unlike traditional model-based approaches, that rely on fitting data to the models, methods of causal discovery determine the causal structure from data. In clinical and EHR data analysis, causal discovery is...
| Main Authors: | , , |
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| 格式: | 文件 |
| 语言: | English |
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IEEE
2024-01-01
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| 丛编: | IEEE Access |
| 主题: | |
| 在线阅读: | https://ieeexplore.ieee.org/document/10457525/ |