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>Isn't this suitable for a Bayesian classifier?

I think that's what GnuCash does by default. Even with years of past transaction data it still gets some very obvious matches wrong for me. In my experience it's about 90% accurate for the ones it really should be able to do based on the training data.



> "...it's about 90% accurate for the ones it really should be able to do based on the training data."

What's the pathway for the remaining 10%? Are they simply misclassified, and dropped into a queue for manual labeling? Do the outliers get managed by the GnuCash? Or do they get dumped into a misc 9000 account?


It shows you the automatic account matches on import, allowing you to double-check and correct any misclassified ones.


Ok. So what you're pointing to is not an automated pipeline, but a user mediated process. It's the same pattern in QuickBooks, or whatever ERP.




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