I am running inference on a Bayesian Network and am receiving the error:
smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros for node...
From reading this forum, it appears that this could be due to either conflicting evidence or a lack of precision (https://support.bayesfusion.com/forum/v ... ries#p3665)
How can I go about diagnosing this issue?
Thanks,
Matt
smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros for
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Re: smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros
Can you share your network and the evidence set?
Re: smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros
Thank you very much for your help. How would you like me to send you the files? I tried to attach the files in a private message within this web forum, but the Bayesian network file is too large.
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Re: smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros
Upload the files somewhere and send me the link in PM.
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Re: smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros
Error -43 you're getting is caused by the loss of precision in the inference algorithm.
Can you limit your target node set? It's not very likely to help in the case of 152 evidence nodes, but it's the only workaround remaining (without changing the structure and/or parameters of your network).
Can you limit your target node set? It's not very likely to help in the case of 152 evidence nodes, but it's the only workaround remaining (without changing the structure and/or parameters of your network).
Re: smile.SMILEException: SMILE error -43 in function UpdateBeliefs. Logged information: All potential entries are zeros
Unfortunately, no I cannot change the structure of the network nor the target nodes. Are the probabilities implemented as log-probabilities (in log space)? If so, I am surprised at the loss of precision. Thanks for your help.