Larry Nedry wrote:
Of course. But how would I figure out what works best? How can I tell if
it is working poorly or very well?
Results.Customer/user complaints are always useful (if perhaps
not really desireable); customer/user *feedback* is critical on
anything bigger than a trivial p
On Wed, May 28, 2008 00:04, Larry Nedry wrote:
> I'm looking for a way to calculate or experimentally find the sweet spot
> for bayes_expiry_max_db_size. Is there an ideal range? Or a maximum size?
> What happens if the size is too high?
what happen is when the size is to big the more ham/spam
On Mittwoch, 28. Mai 2008 Larry Nedry wrote:
> But how would I figure out what works best? How can I tell if
> it is working poorly or very well?
We use bayes_expiry_max_db_size 2123456 and bayes is absolutely correct
for us. I think you cannot really calculate it, it depends on how many
differ
On 5/27/08 at 4:33 PM -0500 Michael Parker wrote:
>You should adjust it for whatever works best for your user base and
>the resources you have available on your database.
Of course. But how would I figure out what works best? How can I tell if
it is working poorly or very well?
I'm looking for
On May 27, 2008, at 4:22 PM, Larry Nedry wrote:
Greetings,
This weekend I created a MySQL db to store my bayes tokens. It
seems to be
working well but I'm a little puzzled by the default size of
bayes_expiry_max_db_size. I understand that the default size is
150,000
which seems very lo
Greetings,
This weekend I created a MySQL db to store my bayes tokens. It seems to be
working well but I'm a little puzzled by the default size of
bayes_expiry_max_db_size. I understand that the default size is 150,000
which seems very low as it took only one day to reach 100,000 tokens.
Was th
