Synthetic Continuous-Time Bayesian Networks
收藏arXiv2025-09-30 收录
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https://github.com/madlabunimib/PyCTBN
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资源简介：
该数据集包含由随机连续时间贝叶斯网络（CTBNs）生成的综合数据，旨在验证所提出的CTPC算法相较于CTSS算法的性能。数据集在不同节点配置、网络密度以及节点状态的情况下生成，这为全面测试学习算法的性能提供了可能。每个网络配置下包含300条轨迹，任务是对CTBNs的结构学习算法进行性能评估。
This dataset contains synthetic data generated by random continuous-time Bayesian networks (CTBNs), which is designed to verify the performance of the proposed CTPC algorithm compared with the CTSS algorithm. The dataset is generated under varying node configurations, network densities and node states, enabling comprehensive performance evaluation of learning algorithms. Each network configuration includes 300 trajectories, and the task is to evaluate the performance of structural learning algorithms for CTBNs.
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