>Why wouldn't we
>want the score be reduced for low confidence?

because the PenaltyBox is working this way - every feature sets, counts, 
calculates or weights results to resulting scores

Calculating/weighting scores base on the Bayes/HMM results is still 
implemented. The next build will use a better code for this.

....
The Bayesian check will only run, if the spam/ham probability of the HMM
check is in a given value range or the HMM check has given too few results 
or
the confidence ( baysConf ) of the detection is too low.
....


How ever you need to configure 'baysConf'! assp will get a probability in 
every case, but this says nothing about the confidence.

Here are two extreme examples:

you can get a probability of 0.650 with a confidence of 0.5 - which is 
100% spam - no doubt
and
you can get a probability of 0.999 with a confidence of 0.00001 - which is 
a very wild guess (50.00001%(spam) to 49.99999%(ham))

'baysConfidenceHalfScore' will reduce the score to at least the half for 
both checks - so the result will be max. the full.

>is correct math, but where do the 12 and 3 numbers come from?

I don't want to discuss the Bayesian/HMM math. These are simple numbers, 
everyone will understand them - less results -> less confidence.
ASSP would not need these numbers, if everyone has a correct corpus 
(corpusnorm). These numbers are something like milestones, if they are 
reached, the code loses trust to the math of the confidence and switches 
the general behavior (block -> score -> monitor). 

I stop this discussion here. Both features are working nearly perfect for 
years now - in my case with less than 0.5% correction rate for each and 
less than 0.25% together, if the corpus is correct.

Thomas 





Von:    K Post <nntp.p...@gmail.com>
An:     ASSP development mailing list <assp-test@lists.sourceforge.net>
Datum:  04.05.2015 18:28
Betreff:        Re: [Assp-test] HMM and Bayesian Running



This is now starting to make more sense to me.  Thank you for the
explanations.

6 = 60 / 12 +1
21 = 60 / 3 +1
is correct math, but where do the 12 and 3 numbers come from?

My BayConf is 0, and intentionally so because my norm is 1.0000 or very
close to that.  That's correct logic right?
And yes, bayesProbability is 0.60

I guess my original question still stands: Why not only count EITHER hmm 
or
bayes if confidence is low on both?  And why would "the confidence is very
low - but it is ignored for the resulting score" be true.  Why wouldn't we
want the score be reduced for low confidence?

Under BayesAfterHMM is says:
The Bayesian check will only run, if the spam/ham probability of the HMM
check is in a given value range or the HMM check has given too few 
results.

Is there an equivalent, easy to implement, and *sensible* solution that is
something like:
HMMScoreDiscardIfOutsideOfRange:
The HMM score will only be counted if the HMM value range is outside of
this range.  Setting this range to something like 0.35-0.65, when paired
with BayesAfterHMM (which will allow Bayesian to run after an HMM check)
stops the HMM score from being added to the bayesian score which would
result in an unreasonably high score.

I'm kind of just thinking out loud here.  Please tell me if what I'm
suggesting doesn't make sense or if I need to be more clear.

On Mon, May 4, 2015 at 3:50 AM, Thomas Eckardt 
<thomas.ecka...@thockar.com>
wrote:

> >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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