>In your example, how is the 6 or 21 number calculated based on a
>maxBayesValues of 60?

6 = 60 / 12 +1
21 = 60 / 3 +1

>I've got BayesAfterHMM set to 0.3-0.7

I assume 'baysProbability' is set to 0.6 - and 'baysConf' is set to zero - 
right ?

If assp got at least 6 but less than 21 results and the resulting HMM 
probability  is for example 0.65  :

- DoHMM is set to score for this mail
- Bayes will run, because 0.65 is less than 0.7 and more than 0.3
- the confidence is very low - but it is ignored for the resulting score
- without 'baysConf',  0.65 is 100% SPAM because  'baysProbability' is set 
to 0.6

The mail gets the full HMM score + the full Bayesian score.


Thomas




Von:    K Post <nntp.p...@gmail.com>
An:     ASSP development mailing list <assp-test@lists.sourceforge.net>
Datum:  03.05.2015 22:15
Betreff:        Re: [Assp-test] HMM and Bayesian Running



In your example, how is the 6 or 21 number calculated based on a
maxBayesValues of 60?

And more importantly, with my example, where there was 49 scored because 
of
HMM, and then another 49 scored for bayesian, also which wasn't
particularly certain.  Net result: a really high score - not really
accurate.  Is there some why to tell ASSP that if HMM and Bayes both 
assign
scores, and HMM is based on a really low number of results, just ignore 
the
HMM result?  I feel like that would be more accurate.

On Sun, May 3, 2015 at 2:55 AM, Thomas Eckardt 
<thomas.ecka...@thockar.com>
wrote:

> It works this way.
>
> For example, if 'maxBayesValues' is set to 60
>
> - DoHMM is set to monitor if less than 6 results are found -> Bayes will
> run
> - DoHMM is set to score, if DoHMM is configured to block and less than 
21
> results are found - Bayes will run on 'BayesAfterHMM'
>
>  Thomas
>
>
>
>
>
>
>
>
> Von:    K Post <nntp.p...@gmail.com>
> An:     ASSP development mailing list <assp-test@lists.sourceforge.net>
> Datum:  02.05.2015 16:34
> Betreff:        [Assp-test] HMM and Bayesian Running
>
>
>
> I've got BayesAfterHMM set to 0.3-0.7
>
> Sometimes, I see bayesian run even though HMM scores a probability of
> 1.00000.  Is that right?  Could this be happening because HMM doesn't 
have
> enough hits?  If that's the case can we tell ASSP to ignore HMM it's
> unsure
> and use Bayesian INSTEAD (only) in these cases?
>
> Sorry for the HMM questions, but the concept's new to me.
>
>
> Clearly my databases aren't quite perfect, but I was hoping that
> senderbase
> would bring the HMM score down enough to pass it.
>
> However, with Bayesian running too, we exceed the max and it's blocked.
>
> X-ASSP-Message-Score: -35 (White Organization/Domain
> 'RESPONSYS')
> X-ASSP-IP-Score: -34 (White Organization/Domain 'RESPONSYS')
> X-ASSP-Detected-URI: rsys2.com(1), e.hotwire.com(1),
> hotwire.com(7)
> X-ASSP-Message-Score: 49 (HMM Probability: 1.0000)
> X-ASSP-IP-Score: 49 (HMM Probability: 1.0000)
> X-ASSP-Message-Score: 49 (Bayesian Probability: 1.00000)
> X-ASSP-IP-Score: 49 (Bayesian Probability: 1.00000)
> X-ASSP-Spam-Prob: 1.00000
> X-ASSP-HMM-Spam-Prob: 1.00000
> X-ASSP-Tag: MessageLimit
> X-ASSP-Spam-Reason: MessageScore 63, limit 50
> X-ASSP-Message-Totalscore: 63
>
> 
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