Re: RE: [Python-Dev] The first trustworthy <wink> GBayes results
Don't count words multiple times, and you'll probably get fewer false positives. That's the main reason I don't do it-- because it magnifies the effect of some random word like water happening to have a big spam probability. (Incidentally, why so high? In my db it's only 0.3930784.) --pg --Tim Peters wrote:
FYI. After cleaning the blatant spam identified by the classifier out of my ham corpus, and replacing it with new random msgs from Barry's corpus, the reported false positive rate fell to about 0.2% (averaging 8 per each batch of 4000 ham test messages). This seems remarkable given that it's ignoring headers, and just splitting the raw text on whitespace in total ignorance of HTML & MIME etc.
'FREE' (all caps) moved into the ranks of best spam indicators. The false negative rate got reduced by a small amount, but I doubt it's a statistically significant reduction (I'll compute that stuff later; I'm looking for Big Things now).
Some of these false positives are almost certainly spam, and at least one is almost certainly a virus: these are msgs that are 100% base64-encoded, or maximally obfuscated quoted-printable. That could almost certainly be fixed by, e.g., decoding encoded text.
The other false positives seem harder to deal with:
+ Brief HMTL msgs from newbies. I doubt the headers will help these get through, as they're generally first-time posters, and aren't replies to earlier msgs. There's little positive content, while all elements of raw HTML have high "it's spam" probability.
Example:
""" --------------=_4D4800B7C99C4331D7B8 Content-Description: filename="text1.txt" Content-Type: text/plain; charset=ISO-8859-1 Content-Transfer-Encoding: quoted-printable
Is there a version of Python with Prolog Extension?? Where can I find it if there is?
Thanks, Luis.
P.S. Could you please reply to the sender too.
--------------=_4D4800B7C99C4331D7B8 Content-Description: filename="text1.html" Content-Type: text/html Content-Transfer-Encoding: quoted-printable
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2//EN"> <HTML> <HEAD> <TITLE>Prolog Extension</TITLE> <META NAME=3D"GENERATOR" CONTENT=3D"StarOffice/5.1 (Linux)"> <META NAME=3D"CREATED" CONTENT=3D"19991127;12040200"> <META NAME=3D"CHANGEDBY" CONTENT=3D"Luis Cortes"> <META NAME=3D"CHANGED" CONTENT=3D"19991127;12044700"> </HEAD> <BODY> <PRE>Is there a version of Python with Prolog Extension?? Where can I find it if there is?
Thanks, Luis.
P.S. Could you please reply to the sender too.</PRE> </BODY> </HTML>
--------------=_4D4800B7C99C4331D7B8--""" """
Here's how it got scored:
prob = 0.999958816093 prob('<META') = 0.957529 prob('<META') = 0.957529 prob('<META') = 0.957529 prob('<BODY>') = 0.979284 prob('Prolog') = 0.01 prob('<HEAD>') = 0.97989 prob('Thanks,') = 0.0337316 prob('Prolog') = 0.01 prob('Python') = 0.01 prob('NAME=3D"GENERATOR"') = 0.99 prob('<HTML>') = 0.99 prob('</HTML>') = 0.989494 prob('</BODY>') = 0.987429 prob('Thanks,') = 0.0337316 prob('Python') = 0.01
Note that '<META' gets penalized 3 times. More on that later.
+ Msgs talking *about* HTML, and including HTML in examples. This one may be troublesome, but there are mercifully few of them.
+ Brief msgs with obnoxious employer-generated signatures. Example:
""" Hi there,
I am looking for you recommendations on training courses available in the UK on Python. Can you help?
Thanks,
Vickie Mills IS Training Analyst
Tel: 0131 245 1127 Fax: 0131 245 1550 E-mail: vickie_mills@standardlife.com
For more information on Standard Life, visit our website http://www.standardlife.com/ The Standard Life Assurance Company, Standard Life House, 30 Lothian Road, Edinburgh EH1 2DH, is registered in Scotland (No SZ4) and regulated by the Personal Investment Authority. Tel: 0131 225 2552 - calls may be recorded or monitored. This confidential e-mail is for the addressee only. If received in error, do not retain/copy/disclose it without our consent and please return it to us. We virus scan all e-mails but are not responsible for any damage caused by a virus or alteration by a third party after it is sent. """
The scoring:
prob = 0.98654879055 prob('our') = 0.928936 prob('sent.') = 0.939891 prob('Tel:') = 0.0620155 prob('Thanks,') = 0.0337316 prob('received') = 0.940256 prob('Tel:') = 0.0620155 prob('Hi') = 0.0533333 prob('help?') = 0.01 prob('Personal') = 0.970976 prob('regulated') = 0.99 prob('Road,') = 0.01 prob('Training') = 0.99 prob('e-mails') = 0.987542 prob('Python.') = 0.01 prob('Investment') = 0.99
The brief human-written part is fine, but the longer boilerplate sig is indistinguishable from spam.
+ The occassional non-Python conference announcement(!). These are long, so I'll skip an example. In effect, it's automated bulk email trying to sell you a conference, so is prone to use the language and artifacts of advertising. Here's typical scoring, for the TOOLS Europe '99 conference announcement:
prob = 0.983583974285 prob('THE') = 0.983584 prob('Object') = 0.01 prob('Bell') = 0.01 prob('Object-Oriented') = 0.01 prob('**************************************************************') = 0.99 prob('Bertrand') = 0.01 prob('Rational') = 0.01 prob('object-oriented') = 0.01 prob('CONTACT') = 0.99 prob('**************************************************************') = 0.99 prob('innovative') = 0.99 prob('**************************************************************') = 0.99 prob('Olivier') = 0.01 prob('VISIT') = 0.99 prob('OUR') = 0.99
Note the repeated penalty for the lines of asterisks. That segues into the next one:
+ Artifacts of that the algorithm counts multiples instances of "a word" multiple times. These are baffling at first sight! The two clearest examples:
"""
Can you create and use new files with dbhash.open()?
Yes. But if I run db_dump on these files, it says "unexpected file type or format", regardless which db_dump version I use (2.0.77, 3.0.55, 3.1.17)
It may be that db_dump isn't compatible with version 1.85 databse files. I can't remember. I seem to recall that there was an option to build 1.85 versions of db_dump and db_load. Check the configure options for BerkeleyDB to find out. (Also, while you are there, make sure that BerkeleyDB was built the same on both of your platforms...)
Try running db_verify (one of the utilities built when you compiled DB) on the file and see what it tells you.
There is no db_verify among my Berkeley DB utilities.
There should have been a bunch of them built when you compiled DB. I've got these:
[Paul Graham]
Don't count words multiple times, and you'll probably get fewer false positives. That's the main reason I don't do it-- because it magnifies the effect of some random word like water happening to have a big spam probability.
Yes, that makes sense, but I'm trained not to think <wink>. Experiment will decide it (although I *expect* it's a good change, and counting multiple occurrences was obviously a factor in several of the rare false positives). If spam really is different, it should be different in several distinct ways.
(Incidentally, why so high? In my db it's only 0.3930784.) --pg
I expect it's because this tokenizer *only* split on whitespace. Punctuation was left intact. So, e.g., on the Python discussion list stuff like The new approach blows it out of the water: and This is very deep water; and Then you'll take to Python like a duck takes to water! are counted as "water:" and "water;" and "water!", not as "water". The spam corpus is chock full o' "water", though: + Porn sites advertising water sports. + Assorted bottled water pitches. + Assorted "oxygenated water" pitches. + Claims of environmental friendliness explicated via stuff like "no harmful chlorine to pollute the water or air!". + Pitches for weight-loss gimmicks emphasizing that you'll really loss fat, not just reduce water retention. + Pitches for weight-loss gimmicks empphasizing that you'll reduce water retention as well as lose fat. + One repeated bizarre analogy for how a breast enlargement cream works in the way "a sponge absorbs water". + This revolutionary new flat garden hose will really cut your water bills. + Ditto this miracle new laundry tablet lets you use a fraction of the water needed by old-fashioned detergents. + Survivalist pitches often mention water in the same sentence as air and medical care. I got tired then <wink>.
FYI, about counting multiple instances of a word multiple times, or only once, when scoring. Changing it to count words only once did fix the specific false positive examples I mentioned. However, across 20 test runs (training on one of five pairs of corpora, and then for each such training pair running predictions across the remaining four pairs), it was a mixed bag. On some runs it appeared to be a real improvement, on others a real regression. Overall, the results didn't support concluding it made a significant difference to the false positive rate, but weakly supported concluding that it increased the false negative rate. That's very tentative -- I didn't stare at the actual misclassifications, I just ran it while sleeping off a flu, then woke up and crunched the numbers. This ignorant-of-MIME tokenization scheme is ridiculously bad for the false negative rate anyway (an entire line of base64 or obfuscated quoted-printable looks like a ham-favoring single "unknown word" to it), so there are bigger fish to fry first.
For what it's worth, the attached (simple) script will 'de-spamassassin' an email message. I use it on my 'spam' folder to get test messages of various ugly MIME things that spam and viruses let through... It's not pretty, but it does the job (for me, anyway) -- Anthony Baxter <anthony@interlink.com.au> It's never too late to have a happy childhood.
(trimming the cc list a bit, since this is drifting a bit away from strictly discussing the current algorithm.) Anthony> For what it's worth, the attached (simple) script will Anthony> 'de-spamassassin' an email message. I use it on my 'spam' Anthony> folder to get test messages of various ugly MIME things that Anthony> spam and viruses let through... Thanks, that helps me as well, as I need to delete the X-VM-* headers Emacs's VM mail package inserts. While spamassassin -d does what you are doing, it can be easily extended to elide other headers as well. One thing worth noting before everybody starts using it to massage their mailboxes is that the email package contains a bug which causes it to occasionally delete whitespace when reformatting headers. For example, in one example, the header went from Received: from rogers.com ([24.43.65.252]) by fep02-mail.bloor.is.net.cable.rogers.com (InterMail vM.5.01.05.06 201-253-122-126-106-20020509) with ESMTP id <20020820205424.DFHH4777.fep02-mail.bloor.is.net.cable.rogers.com@rogers.com>; Tue, 20 Aug 2002 16:54:24 -0400 to Received: from rogers.com ([24.43.65.252]) by fep02-mail.bloor.is.net.cable.rogers.com (InterMail vM.5.01.05.06 201-253-122-126-106-20020509) with ESMTPid <20020820205424.DFHH4777.fep02-mail.bloor.is.net.cable.rogers.com@rogers.com>; Tue, 20 Aug 2002 16:54:24 -0400 Note that in the second version there is no space between "ESMTP" and "id", which had previously been separated by a newline and several spaces. I filed a bug report about it a few days ago: http://python.org/sf/594893 Skip
Skip Montanaro wrote One thing worth noting before everybody starts using it to massage their mailboxes is that the email package contains a bug which causes it to occasionally delete whitespace when reformatting headers.
There's one other known problem - seriously misformatted MIME (as seen in spam, and email from Microsoft Entourage) causes the email package to barf out. I plan, at some point, to try and make a "if it fails, just leave the body as one chunk of text" mode, but it's a long long way down my list of priorities. -- Anthony Baxter <anthony@interlink.com.au> It's never too late to have a happy childhood.
"AB" == Anthony Baxter <anthony@interlink.com.au> writes:
>> Skip Montanaro wrote >> One thing worth noting before everybody starts using it to >> massage their mailboxes is that the email package contains a >> bug which causes it to occasionally delete whitespace when >> reformatting headers. BTW, I fixed Greg's problem but not Skip's. I'm still looking at this one... AB> There's one other known problem - seriously misformatted MIME AB> (as seen in spam, and email from Microsoft Entourage) causes AB> the email package to barf out. I plan, at some point, to try AB> and make a "if it fails, just leave the body as one chunk of AB> text" mode, but it's a long long way down my list of AB> priorities. I just checked this into cvs. -Barry
participants (5)
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Anthony Baxter -
barry＠python.org -
Paul Graham -
Skip Montanaro -
Tim Peters