Update error
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Re: Update error
If your evolutionary algorithm produces very complex networks, switch inference algorithm to EPIS (inexact, sampling-based but quire reliable). You may want to adjust the number of samples, use Network.SampleCount property for this.
Re: Update error
Good afternoon,
Do you suggest that I put Network.SampleCount = number of nodes?
Thank you.
Do you suggest that I put Network.SampleCount = number of nodes?
Thank you.
Re: Update error
Good Morning,shooltz[BayesFusion] wrote: ↑Tue Apr 28, 2020 2:48 pm If your evolutionary algorithm produces very complex networks, switch inference algorithm to EPIS (inexact, sampling-based but quire reliable). You may want to adjust the number of samples, use Network.SampleCount property for this.
I used this method and the error still persisted.
The problem is that I cannot further reduce the amount of information.
There are 42 nodes where each time I insert information at least 50 different information is multiplied by 800x. This is the least I can work on.
Unfortunately I was not able to work with all this data.
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- Site Admin
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Re: Update error
Are you sure you got the same error when inference algorithm was set to EPIS?I used this method and the error still persisted.
BTW, Network.SampleCount defaults to 10000 and can be made much larger. Increasing the sample count does not require more memory, but it makes the inference run longer and produce more accurate results.
Re: Update error
unfortunately the error occurred yes, net.BayesianAlgorithm = Network.BayesianAlgorithmType.EpisSampling ;.shooltz[BayesFusion] wrote: ↑Wed May 13, 2020 1:27 pmAre you sure you got the same error when inference algorithm was set to EPIS?I used this method and the error still persisted.
BTW, Network.SampleCount defaults to 10000 and can be made much larger. Increasing the sample count does not require more memory, but it makes the inference run longer and produce more accurate results.
At first I don't need anything very precise, but rather fast. My file has 40000 pieces of information and for each sample I duplicate it 800x, 50 different samples being 50x800. I perform around 840000 update and inference, 400 Baysian network.
I'm running 1050 tests like this on a Gcloud server right now.