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I am training a Bayesian Network (BN) containing 12 attributes with a 10,002,716 rows × 12 columns dataset. The structure of this BN model would be chow-liu tree, where each attribute has maximum one parent. Some of my attributes have relative large number of states (e.g., 3000) so I know training could take a long time. Since I have waited for the training result for an hour and the learning is still continuing, I wonder what is the reasonable BN learning time range for BayesNets.jl. I am a bit concerned the training will cause "out of memory" problem.
Thank you for help!
The text was updated successfully, but these errors were encountered:
Hi,
I am training a Bayesian Network (BN) containing 12 attributes with a 10,002,716 rows × 12 columns dataset. The structure of this BN model would be chow-liu tree, where each attribute has maximum one parent. Some of my attributes have relative large number of states (e.g., 3000) so I know training could take a long time. Since I have waited for the training result for an hour and the learning is still continuing, I wonder what is the reasonable BN learning time range for BayesNets.jl. I am a bit concerned the training will cause "out of memory" problem.
Thank you for help!
The text was updated successfully, but these errors were encountered: