Causality:回购因果关系研究

上传者: 42097533 | 上传时间: 2023-04-07 10:12:22 | 文件大小: 310KB | 文件类型: ZIP
因果框架 HPCC系统因果关系框架目前正在开发中。 该存储库提供了一个Python模块,该模块实现了因果模型表示,验证,因果推理以及最终反事实推理的所有相关算法。 它具有综合的数据生成功能,可用于测试算法并针对各种情况探查其功能。 该存储库可用作独立的Python框架。 它还将用于为HPCC Systems超级计算集群上的并行因果框架提供本地处理。 有关因果关系,因果推断以及各种因果算法的详细信息,请参见下面的参考部分。 安装 先决条件 Python3 麻木 matplotlib 程序 克隆存储库 将您的存储库添加到pythonpath或在存储库中工作。 因果方法 cGraph.py (因果图)是系统的心脏。 它接受一个多元数据集以及一个因果模型(也称为路径图),该模型被认为与产生数据的因果过程相对应。 因果模型是有向无环图,它代表了因果过程的最佳假设,该假设是所提供数据集生成的基础。

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