Dňa 19. septembra 2022 20:45:27 UTC používateľ Brandon Long <bl...@google.com> napísal:
>The simple answer is you add that signal to the list of other signals in >your machine learning >model and let the model training figure out how useful it is as a signal >and what to combine >it with. Depending on the type of ML, you may or may not be able to see in >the model the >utility of the specific signal. I did some experiments with rspamd's neural module recently, but the results had too high false positives (up to 25 %). I cannot decide, if its model fails or here was low messages count in learn stage or i configure it wrong, or whatever else. But with this result, it is not reliably usable for me, and i cannot build anything based on its results. I am not aware of any other thool, which one can "simple use" in mail processing. And to learn it from scratch and to build my own model/tool i have not enough time nor knowledge nor experiences in that. Anyway, i do not believe the machine learning systems mostly, when i consider that it will have bugs in code, bugs in models (as any SW has) and mistakes in learning, that is not something what i want to rely on it, despite that it is big bussword nowadays. regards -- Slavko https://www.slavino.sk/ _______________________________________________ mailop mailing list mailop@mailop.org https://list.mailop.org/listinfo/mailop
