On Mon, 22 Aug 2011 15:46:14 +0200, J4K wrote:
# sa-learn --dump magic
0.000 0 3 0 non-token data: bayes db
version
0.000 0 640 0 non-token data: nspam
0.000 0 7001 0 non-token data: nham
0.000 0 366899 0 non-token data: ntokens
its not really possible to say if one nham is one ntokens, and same
goes for nspam, so in all its not possible to know if it bad learned
either, but keep monitoring it so says if rbl testing in mta is doing a
rate of bayes learn, test one spam, test one ham, if bayes agre then its
learned correct
basicly one should learn all msgs, not just the ones that is learned
bad, this keeps more tokens vaigthed good so false is reduced that way
bayes lives in a very dynamic world :=)
