> Bayesian matching tokenizes the description on whitespace. Each time you > assign a transaction whose description contains a particular token the count > on the corresponding token-account pair is incremented (and the token-account > pair is created if it doesn’t already exist). There’s no filtering applied to > the tokens; that might be a useful enhancement. > > Matching is accomplished by finding all of the token-account pairs matching > the tokens in the transaction’s description and then summing the counts by > account. The account with the highest sum is assigned as the match. > > Regards, > John Ralls
Based on this explanation, and on the FAQ question about “How do I get the most benefit from the Bayesian learning algorithm while importing?” (https://wiki.gnucash.org/wiki/FAQ#Q:_How_do_I_get_the_most_benefit_from_the_Bayesian_learning_algorithm_while_importing.3F <https://wiki.gnucash.org/wiki/FAQ#Q:_How_do_I_get_the_most_benefit_from_the_Bayesian_learning_algorithm_while_importing.3F>), and on the fact that when I started with GNUCash I ignored the import dialog because I found entering the account information into the register after import to be faster than using the import dialog; I should delete *all* the Beyesian information in the import dialog for all accounts. My understanding is that I have an invalid set of data, because I have broken a fundamental assumption - the human has correctly mapped transactions to accounts. I imported easily 100s of transactions without mapping. Thanks!, Justin _______________________________________________ gnucash-user mailing list gnucash-user@gnucash.org To update your subscription preferences or to unsubscribe: https://lists.gnucash.org/mailman/listinfo/gnucash-user If you are using Nabble or Gmane, please see https://wiki.gnucash.org/wiki/Mailing_Lists for more information. ----- Please remember to CC this list on all your replies. You can do this by using Reply-To-List or Reply-All.
