Py-Tetrad和RPy-Tetrad:一个新的Python接口与R支持Tetrad因果搜索
Joseph D Ramsey1, Bryan Andrews2
1Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA.
Proceedings of machine learning research
|August 12, 2024
概括
新的Python和R接口使研究人员能够轻松访问Tetrad项目的因果发现算法. 这些新的工具弥合了统计软件和既有因果建模软件之间的差距,简化了复杂的分析.
科学领域:
- 计算统计的计算统计.
- 因果推理的原因推理.
- 机器学习是机器学习.
背景情况:
- 泰特拉德项目是一个长期存在的,用于因果发现,搜索和估计的全面软件套件,PC和FCI等算法是基础的.
- 现有的将Tetrad基于Java的功能与Python和R等流行的数据分析环境集成的方法不足以满足当前的研究需求.
研究的目的:
- 为Tetrad项目开发和介绍新的,用户友好的Python和R接口.
- 从Python和R环境中方便直接访问Tetrad的高级因果建模算法.
主要方法:
- 利用 JPype Python-Java 接口将 Python 与 Tetrad 的 Java 代码库连接起来.
- 使用Reticulate Python-R接口实现R和Python之间的互操作性,从而访问Tetrad功能.
- 开发了补充工具并提供了工作示例,以确保简单的集成和使用.
主要成果:
- 成功为Python和R创建了强大而直观的界面,以便与Tetrad项目进行交互.
- 证明了JPype和Reticulate在访问Tetrad的因果发现和估计算法方面的易用性和有效性.
结论:
- 新的接口显著提高了使用Python和R的研究人员对Tetrad强大的因果建模能力的可访问性.
- 这些进步简化了因果发现工作流程,使复杂的因果推理方法在主流统计软件中更容易获得.
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