图 书 馆
通过比较干预分布来评估因果模型Evaluating Causal Models by Comparing Interventional Distributions |
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| 课程网址: | https://videolectures.net/videos/kdd2016_garant_interventional_di... |
| 主讲教师: | Dan Garant |
| 开课单位: | KDD 2016研讨会 |
| 开课时间: | 2016-10-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The predominant method for evaluating the quality of causal models is to measure the graphical accuracy of the learned model structure. We present an alternative method for evaluating causal models that directly measures the accuracy of estimated interventional distributions. We contrast such distributional measures with structural measures, such as structural Hamming distance and structural intervention distance, showing that structural measures often correspond poorly to the accuracy of estimated interventional distributions. We use a number of real and synthetic datasets to illustrate various scenarios in which structural measures provide misleading results with respect to algorithm selection and parameter tuning, and we recommend that distributional measures become the new standard for evaluating causal models. |
| 关 键 词: | 干预分布; 因果模型; 图形精度 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-01-04：liyq |
| 最后编审: | 2025-01-04：liyq |
| 阅读次数: | 9 |