Synthetic Data for GraphNOTEARS

该数据集是基于结构方程模型（SEM）生成的，该模型模拟了现实世界的场景，并采用了已知的生成机制。数据集包含了多种图形生成模型，如厄多斯-雷尼模型（Erdős-Rényi）和巴拉巴西-阿尔伯特模型（Barabási-Albert），并涵盖了带权重的层内和层间图形。其规模根据参数n和d的不同而有所变化，该数据集的任务是进行因果结构学习。

This dataset is generated based on the Structural Equation Model (SEM), which simulates real-world scenarios and adopts known generative mechanisms. It includes various graph generative models, such as the Erdős-Rényi model and the Barabási-Albert model, and covers weighted intra-layer and inter-layer graphs. Its scale varies depending on the values of parameters n and d, and the task of this dataset is causal structure learning.