Goodness of Causal Fit
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We propose a Goodness of Causal Fit (GCF) measure which depends on Pearl "do" interventions. This is different from a measure of Goodness of Fit (GF), which does not use interventions. Given a DAG set G, to find a good G∈ G, we propose plotting GCF(G) versus GF(G) for all G∈ G, and finding a graph G∈ G with a large amount of both types of goodness.
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