On Thursday 21 January 2016 at 13:11:15, RW wrote:
> On Wed, 20 Jan 2016 22:21:49 -0800 Marc Perkel wrote:
> > OK - Just to show you this isn't Bayesian - see if you can do this.
> >
> > Here is a list of 5505874 words and phrases used in the subject line
> > of HAM and never seen in the subject line of SPAM
> >
> > http://www.junkemailfilter.com/data/subject-ham.txt
> >
> > Here is a list of 3494938 words and phrases used in the subject line
> > of SPAM and never seen in the subject line of HAM
> >
> > http://www.junkemailfilter.com/data/subject-spam.txt
> >
> > Hope you understand it now. Not Bayesian!!!!
>
> the only difference between
>
>
> "ambulatory care" -> only in ham
> "aall cards" -> only in spam
>
> and
>
> "ambulatory care" occurs 16 times in ham and 0 times in spam
>
> "aall cards" occurs 0 times in ham and 3 times in spam
>
> is that you have discarded the count information.
Plus, the "never in ham" and "never in spam" lists omit any mention of words &
phrases which exist in differing proportions in both - Bayes includes that, and
I would expect that a spam identifier which takes account of as many known
charactersistics of spam/ham as possible is going to do the best job.
Antony.
--
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The customer gets to pick any two out of three.
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