|Table of Contents|

Fast causal network skeleton learning algorithm

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2016年03期
Page:
315-
Research Field:
Publishing date:

Info

Title:
Fast causal network skeleton learning algorithm
Author(s):
Hong Yinghan
School of Physics and Electronic Engineering,Hanshan Normal University,Chaozhou 521041,China
Keywords:
causal networks skeletons high dimensional networks causal sets conditional independence tests
PACS:
TP181
DOI:
10.14177/j.cnki.32-1397n.2016.40.03.011
Abstract:
Aiming at the problem that the traditional structure of causal network learning algorithms is unfit for high dimensional networks,a fast causal network skeleton construction algorithm is proposed for high dimensional networks.A mutual information accelerating strategy is used based on the maximum dependence and the minimum redundancy,two candidate causal sets between two nodes are found out,and conditional independence tests of the 2 nodes are proposed in the union of the 2 candidate causal sets.Real data experiments show that the time complexity of the algorithm proposed here is better than the traditional algorithms for high dimensional networks; the recognition accuracy of networks is improved because conditional independence tests are decreased.

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Last Update: 2016-06-30