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公开(公告)号:EP3770920A1
公开(公告)日:2021-01-27
申请号:EP20187789.1
申请日:2020-07-24
发明人: LEE, Ciarán Mark , DHIR, Anish
摘要: A computer implemented method of creating a model that is a graphical representation comprising:
receiving, a first dataset comprising a first variable and a third variable and a second dataset comprising a second variable and the third variable;
creating graphical representations of the first dataset and the second dataset by applying conditional independence tests on the first dataset and second dataset;
storing conditional independence information obtained by applying the conditional independence tests on the first dataset and the second dataset;
applying a bivariate causal discovery algorithm to determine a causal relation between the first and third variable in the first dataset and a causal relation between the second and third variable in the second dataset, the causal discovery algorithm being able to determine if the first variable causes the third variable, the third variable causes the first variable, the second variable causes the third variable and the third variable causes the second variable;
modifying the graphical representations of the first and second dataset according to the determined causal relations; and
creating a set of candidate graphical representations for a third dataset comprising the first dataset and the second dataset, wherein each candidate graphical representation is consistent with the conditional independence information.