Hi Tiago, Thank you for that explanation. A quick follow-up:
If calculating likelihoods of both missing and spurious edges would I expect the output to be on a continuous scale of existence likelihood? Assume there is an edge “c” which I am assuming to be a missing edge and I calculate the likelihood ratios by summing across all three edges (based on `s.get_edges_prob([],[a], entropy_args=dict(partition_dl=False))`, `s.get_edges_prob([],[b], entropy_args=dict(partition_dl=False))` and `s.get_edges_prob([c],[], entropy_args=dict(partition_dl=False))`). If I find \lambda_a > \lambda_c > \lambda_b can I read this that “a” is more likely to be spurious than “c” is to be missing (which in turn is more likely to be spurious than "b" is to be missing)? Or is such a comparison not really meaningful anyways? Best, Philipp _______________________________________________ graph-tool mailing list [email protected] https://lists.skewed.de/mailman/listinfo/graph-tool
