An efficient causal structure learning algorithm for linear arbitrarily distributed continuous data

作者：Yang, Jing; Li, Na; An, Ning^*; Chen, Yu; Alterovitz, Gil

来源：Journal of Supercomputing, 2020, 76(5): 3355-3363.

DOI：10.1007/s11227-018-2557-5

• Causal discovery
• Simultaneous equations model
• Arbitrary distribution

Aim to the linear arbitrarily distributed continuous data, an causal structure learning algorithm BSEM, which is based on simultaneous equations model, was presented. The algorithm merges together simultaneous equations model and local learning. The contribution of this paper is that for linear arbitrarily distributed datasets, BSEM algorithm can effectively learn the causal structure from the datasets. We used the Sociology data to do experiments, and results demonstrated that BSEM displays good accuracy and time performance.

• 出版日期2020-5
• 单位合肥工业大学; 中国科学技术大学