Aiming at the order dependency problem of the K2 algorithm, this paper proposed a heuristic algorithm(H-vnK2) to learn the node order effectively from a given data set. Specifically, based on the v-structure knowledge learned by the PC algorithm, it corrected the order of some parent-child nodes in the form of node blocks quickly and accurately, and then obtained the optimal order of some nodes. Based on the neighbor set knowledge learned by the PC algorithm, with the distance threshold heuristic strategy, it further modified the order of the parent-child nodes from the global optimal point of view, and then obtained the best order of all nodes. Experiments show that the proposed algorithm is significantly better than the comparison algorithm on the Asia and Alarm standard data set. Among them, compared with the best-performing method based on causal effects, the proposed algorithm improves the accuracy rate by 7% on average, and the increment can reach up to 33.3%. It can learn a more accurate network structure.

[2021-09-19] Accepted Paper /doc/2021.07.0273/v1

[2022-02-05] Printed Article /doc/2021.07.0273/v2