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I am currently trying to replicate the performance metrics published in your paper. I used the test.py script with the provided model_bpCL.pt weights on the test_graph.pt data. However, I encountered a significant discrepancy in the Fmax value; I obtained an Fmax of 0.379, which is quite different from the expected 0.595 as reported.
I have set up the environment exactly as specified in the environment.yml and followed the other setup instructions as given.
I have attached a screenshot of the test results for your reference. Could you please help me understand what might be causing this issue? Is there any step or configuration that I might be missing?
The text was updated successfully, but these errors were encountered:
I'm sorry that the Fmax and AUPR provided by the test script confuse you. The standard evaluation script is "evaluation_matrics.py", which consider all the accept threshold (probability between 0.01-0.99), as well as the ancestor function filling.
Hello,
I am currently trying to replicate the performance metrics published in your paper. I used the
test.py
script with the providedmodel_bpCL.pt
weights on thetest_graph.pt
data. However, I encountered a significant discrepancy in the Fmax value; I obtained an Fmax of 0.379, which is quite different from the expected 0.595 as reported.I have set up the environment exactly as specified in the
environment.yml
and followed the other setup instructions as given.I have attached a screenshot of the test results for your reference. Could you please help me understand what might be causing this issue? Is there any step or configuration that I might be missing?
The text was updated successfully, but these errors were encountered: