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Posted to sysadmins@spamassassin.apache.org by Cron Daemon <ro...@sa-vm1.apache.org> on 2019/10/06 03:33:44 UTC

Cron ~/svn/trunk/build/mkupdates/do-stable-update-with-scores force | /usr/bin/tee /usr/local/spamassassin/automc/tmp/do-stable-update-with-scores.log

+ echo ''\''Running do-nightly-rescore-example.sh ...'
+ echo ''
+ /usr/local/spamassassin/automc/svn/trunk/masses/rule-update-score-gen/do-nightly-rescore-example.sh force
'Running do-nightly-rescore-example.sh ...

Beginning of Week.  Running with 0 first.
/usr/local/spamassassin/automc/tmp/generate-new-scores
Sun Oct  6 02:25:09 UTC 2019
[ rsyncing logs ]
[ rsyncing logs locally ]
sending incremental file list
ham-axb-coi-bulk.r1867918.log
ham-axb-coi-bulk.r1867965.log
ham-axb-generic.r1867918.log
ham-axb-generic.r1867965.log
ham-axb-ham-misc.r1867918.log
ham-axb-ham-misc.r1867965.log
ham-darxus.r1867918.log
ham-darxus.r1867965.log
ham-ena-week3.r1867918.log
ham-ena-week3.r1867965.log
ham-ena-week4.r1867918.log
ham-ena-week4.r1867965.log
ham-giovanni-ham.r1867918.log
ham-giovanni-ham.r1867965.log
ham-giovanni-spam.r1867918.log
ham-giovanni-spam.r1867965.log
ham-giovanni-spammy.r1867918.log
ham-giovanni-spammy.r1867965.log
ham-grenier.r1867918.log
ham-grenier.r1867965.log
ham-hege.r1867918.log
ham-hege.r1867965.log
ham-jarif.r1867918.log
ham-jarif.r1867965.log
ham-jbrooks.r1867918.log
ham-jbrooks.r1867965.log
ham-llanga.r1867918.log
ham-llanga.r1867965.log
ham-mmiroslaw-mails-ham.r1867918.log
ham-mmiroslaw-mails-ham.r1867965.log
ham-mmiroslaw-mails-spam.r1867918.log
ham-mmiroslaw-mails-spam.r1867965.log
ham-net-axb-coi-bulk.r1867656.log
ham-net-axb-coi-bulk.runknown.log
ham-net-axb-generic.r1867656.log
ham-net-axb-generic.runknown.log
ham-net-axb-ham-misc.r1867656.log
ham-net-axb-ham-misc.runknown.log
ham-net-darxus.r1867656.log
ham-net-darxus.runknown.log
ham-net-ena-week0.runknown.log
ham-net-ena-week2.r1867656.log
ham-net-ena-week3.r1867656.log
ham-net-ena-week3.runknown.log
ham-net-ena-week4.r1867656.log
ham-net-ena-week4.runknown.log
ham-net-grenier.r1867656.log
ham-net-grenier.runknown.log
ham-net-hege.r1867656.log
ham-net-hege.runknown.log
ham-net-jarif.r1867656.log
ham-net-jarif.runknown.log
ham-net-jbrooks.r1867656.log
ham-net-jbrooks.runknown.log
ham-net-llanga.r1867656.log
ham-net-mmiroslaw-mails-ham.r1867656.log
ham-net-mmiroslaw-mails-ham.runknown.log
ham-net-mmiroslaw-mails-spam.r1867656.log
ham-net-mmiroslaw-mails-spam.runknown.log
ham-net-npiazzi.r1867656.log
ham-net-npiazzi.runknown.log
ham-net-pds.r1867656.log
ham-net-pds.runknown.log
ham-net-sihde.r1867656.log
ham-net-sihde.runknown.log
ham-net-spamsponge.r1867656.log
ham-net-spamsponge.runknown.log
ham-net-thendrikx.r1867656.log
ham-net-thendrikx.runknown.log
ham-npiazzi.r1867918.log
ham-npiazzi.r1867965.log
ham-pds.r1867918.log
ham-pds.r1867965.log
ham-sihde.r1867918.log
ham-sihde.r1867965.log
ham-spamsponge.r1867918.log
ham-spamsponge.r1867965.log
ham-thendrikx.r1867918.log
ham-thendrikx.r1867965.log
spam-axb-coi-bulk.r1867918.log
spam-axb-coi-bulk.r1867965.log
spam-axb-generic.r1867918.log
spam-axb-generic.r1867965.log
spam-axb-ham-misc.r1867918.log
spam-axb-ham-misc.r1867965.log
spam-darxus.r1867918.log
spam-darxus.r1867965.log
spam-ena-week3.r1867918.log
spam-ena-week3.r1867965.log
spam-ena-week4.r1867918.log
spam-ena-week4.r1867965.log
spam-giovanni-ham.r1867918.log
spam-giovanni-ham.r1867965.log
spam-giovanni-spam.r1867918.log
spam-giovanni-spam.r1867965.log
spam-giovanni-spammy.r1867918.log
spam-giovanni-spammy.r1867965.log
spam-grenier.r1867918.log
spam-grenier.r1867965.log
spam-hege.r1867918.log
spam-hege.r1867965.log
spam-jarif.r1867918.log
spam-jarif.r1867965.log
spam-jbrooks.r1867918.log
spam-jbrooks.r1867965.log
spam-llanga.r1867918.log
spam-llanga.r1867965.log
spam-mmiroslaw-mails-ham.r1867918.log
spam-mmiroslaw-mails-ham.r1867965.log
spam-mmiroslaw-mails-spam.r1867918.log
spam-mmiroslaw-mails-spam.r1867965.log
spam-net-axb-coi-bulk.r1867656.log
spam-net-axb-coi-bulk.runknown.log
spam-net-axb-generic.r1867656.log
spam-net-axb-generic.runknown.log
spam-net-axb-ham-misc.r1867656.log
spam-net-axb-ham-misc.runknown.log
spam-net-darxus.r1867656.log
spam-net-darxus.runknown.log
spam-net-ena-week0.runknown.log
spam-net-ena-week2.r1867656.log
spam-net-ena-week3.r1867656.log
spam-net-ena-week3.runknown.log
spam-net-ena-week4.r1867656.log
spam-net-ena-week4.runknown.log
spam-net-grenier.r1867656.log
spam-net-grenier.runknown.log
spam-net-hege.r1867656.log
spam-net-hege.runknown.log
spam-net-jarif.r1867656.log
spam-net-jarif.runknown.log
spam-net-jbrooks.r1867656.log
spam-net-jbrooks.runknown.log
spam-net-llanga.r1867656.log
spam-net-mmiroslaw-mails-ham.r1867656.log
spam-net-mmiroslaw-mails-ham.runknown.log
spam-net-mmiroslaw-mails-spam.r1867656.log
spam-net-mmiroslaw-mails-spam.runknown.log
spam-net-npiazzi.r1867656.log
spam-net-npiazzi.runknown.log
spam-net-pds.r1867656.log
spam-net-pds.runknown.log
spam-net-sihde.r1867656.log
spam-net-sihde.runknown.log
spam-net-spamsponge.r1867656.log
spam-net-spamsponge.runknown.log
spam-net-thendrikx.r1867656.log
spam-net-thendrikx.runknown.log
spam-npiazzi.r1867918.log
spam-npiazzi.r1867965.log
spam-pds.r1867918.log
spam-pds.r1867965.log
spam-sihde.r1867918.log
spam-sihde.r1867965.log
spam-spamsponge.r1867918.log
spam-spamsponge.r1867965.log
spam-thendrikx.r1867918.log
spam-thendrikx.r1867965.log

sent 30,999,295,529 bytes  received 3,018 bytes  62,435,646.62 bytes/sec
total size is 30,991,718,032  speedup is 1.00
Sun Oct  6 02:33:25 UTC 2019
[ selecting log files to use for scoreset 0 ]
Linked spam-spamsponge.r1867965.log to corpus/usable-corpus-set0/spam-spamsponge.r1867965.log
Linked spam-mmiroslaw-mails-spam.r1867965.log to corpus/usable-corpus-set0/spam-mmiroslaw-mails-spam.r1867965.log
Linked spam-axb-coi-bulk.r1867965.log to corpus/usable-corpus-set0/spam-axb-coi-bulk.r1867965.log
Linked spam-ena-week4.r1867965.log to corpus/usable-corpus-set0/spam-ena-week4.r1867965.log
Linked ham-ena-week4.r1867965.log to corpus/usable-corpus-set0/ham-ena-week4.r1867965.log
Linked spam-mmiroslaw-mails-ham.r1867965.log to corpus/usable-corpus-set0/spam-mmiroslaw-mails-ham.r1867965.log
Linked ham-mmiroslaw-mails-spam.r1867965.log to corpus/usable-corpus-set0/ham-mmiroslaw-mails-spam.r1867965.log
Linked ham-axb-coi-bulk.r1867965.log to corpus/usable-corpus-set0/ham-axb-coi-bulk.r1867965.log
Linked spam-jarif.r1867965.log to corpus/usable-corpus-set0/spam-jarif.r1867965.log
Linked ham-darxus.r1867965.log to corpus/usable-corpus-set0/ham-darxus.r1867965.log
Linked spam-jbrooks.r1867965.log to corpus/usable-corpus-set0/spam-jbrooks.r1867965.log
Linked spam-giovanni-spam.r1867965.log to corpus/usable-corpus-set0/spam-giovanni-spam.r1867965.log
Linked spam-giovanni-ham.r1867965.log to corpus/usable-corpus-set0/spam-giovanni-ham.r1867965.log
Linked ham-sihde.r1867965.log to corpus/usable-corpus-set0/ham-sihde.r1867965.log
Linked ham-ena-week3.r1867965.log to corpus/usable-corpus-set0/ham-ena-week3.r1867965.log
Linked ham-giovanni-spammy.r1867965.log to corpus/usable-corpus-set0/ham-giovanni-spammy.r1867965.log
Linked ham-hege.r1867965.log to corpus/usable-corpus-set0/ham-hege.r1867965.log
Linked spam-axb-ham-misc.r1867965.log to corpus/usable-corpus-set0/spam-axb-ham-misc.r1867965.log
Linked spam-grenier.r1867965.log to corpus/usable-corpus-set0/spam-grenier.r1867965.log
Linked spam-llanga.r1867965.log to corpus/usable-corpus-set0/spam-llanga.r1867965.log
Linked spam-pds.r1867965.log to corpus/usable-corpus-set0/spam-pds.r1867965.log
Linked spam-sihde.r1867965.log to corpus/usable-corpus-set0/spam-sihde.r1867965.log
Linked spam-ena-week3.r1867965.log to corpus/usable-corpus-set0/spam-ena-week3.r1867965.log
Linked ham-grenier.r1867965.log to corpus/usable-corpus-set0/ham-grenier.r1867965.log
Linked spam-darxus.r1867965.log to corpus/usable-corpus-set0/spam-darxus.r1867965.log
Linked spam-hege.r1867965.log to corpus/usable-corpus-set0/spam-hege.r1867965.log
Linked ham-pds.r1867965.log to corpus/usable-corpus-set0/ham-pds.r1867965.log
Linked ham-llanga.r1867965.log to corpus/usable-corpus-set0/ham-llanga.r1867965.log
Linked ham-spamsponge.r1867965.log to corpus/usable-corpus-set0/ham-spamsponge.r1867965.log
Linked ham-giovanni-spam.r1867965.log to corpus/usable-corpus-set0/ham-giovanni-spam.r1867965.log
Linked ham-npiazzi.r1867965.log to corpus/usable-corpus-set0/ham-npiazzi.r1867965.log
Linked ham-axb-ham-misc.r1867965.log to corpus/usable-corpus-set0/ham-axb-ham-misc.r1867965.log
Linked ham-mmiroslaw-mails-ham.r1867965.log to corpus/usable-corpus-set0/ham-mmiroslaw-mails-ham.r1867965.log
Linked ham-axb-generic.r1867965.log to corpus/usable-corpus-set0/ham-axb-generic.r1867965.log
Linked ham-giovanni-ham.r1867965.log to corpus/usable-corpus-set0/ham-giovanni-ham.r1867965.log
Linked ham-jbrooks.r1867965.log to corpus/usable-corpus-set0/ham-jbrooks.r1867965.log
Linked spam-thendrikx.r1867965.log to corpus/usable-corpus-set0/spam-thendrikx.r1867965.log
Linked spam-npiazzi.r1867965.log to corpus/usable-corpus-set0/spam-npiazzi.r1867965.log
Linked spam-axb-generic.r1867965.log to corpus/usable-corpus-set0/spam-axb-generic.r1867965.log
Linked ham-thendrikx.r1867965.log to corpus/usable-corpus-set0/ham-thendrikx.r1867965.log
Linked ham-jarif.r1867965.log to corpus/usable-corpus-set0/ham-jarif.r1867965.log
Linked spam-giovanni-spammy.r1867965.log to corpus/usable-corpus-set0/spam-giovanni-spammy.r1867965.log

Majority SVN revision found: 1867965

Checking corpus/usable-corpus-set0/spam-spamsponge.r1867965.log for SVN 1867965...
# SVN revision: 1867965
Checking corpus/usable-corpus-set0/spam-mmiroslaw-mails-spam.r1867965.log for SVN 1867965...
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Checking corpus/usable-corpus-set0/spam-ena-week4.r1867965.log for SVN 1867965...
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# SVN revision: 1867965
 HAM CONTRIBUTORS FOUND: 21 (required 8)
SPAM CONTRIBUTORS FOUND: 21 (required 8)
Sun Oct  6 02:33:26 UTC 2019
[ checking out code from svn repository ]
+ svn co -r 1867965 http://svn.apache.org/repos/asf/spamassassin/trunk trunk-new-rules-set0
A    trunk-new-rules-set0/rules
A    trunk-new-rules-set0/INSTALL.VMS
A    trunk-new-rules-set0/rules/60_whitelist.cf
A    trunk-new-rules-set0/rules/v312.pre
A    trunk-new-rules-set0/rules/25_dkim.cf
A    trunk-new-rules-set0/rules/v342.pre
A    trunk-new-rules-set0/rules/active.list
A    trunk-new-rules-set0/rules/60_whitelist_auth.cf
A    trunk-new-rules-set0/rules/30_text_fr.cf
A    trunk-new-rules-set0/rules/20_mailspike.cf
A    trunk-new-rules-set0/rules/v310.pre
A    trunk-new-rules-set0/rules/60_whitelist_spf.cf
A    trunk-new-rules-set0/rules/STATISTICS-set2.txt
A    trunk-new-rules-set0/rules/30_text_de.cf
A    trunk-new-rules-set0/sa-update.raw
A    trunk-new-rules-set0/MANIFEST.SKIP
A    trunk-new-rules-set0/sa-compile.raw
A    trunk-new-rules-set0/NOTICE
A    trunk-new-rules-set0/LICENSE
A    trunk-new-rules-set0/PACKAGING
A    trunk-new-rules-set0/rules/STATISTICS-set1.txt
A    trunk-new-rules-set0/rules/25_dnswl.cf
A    trunk-new-rules-set0/rules/20_freemail_mailcom_domains.cf
A    trunk-new-rules-set0/Makefile.PL
A    trunk-new-rules-set0/sa-check_spamd.raw
A    trunk-new-rules-set0/rules/svn_only.pre
A    trunk-new-rules-set0/rules/20_ratware.cf
A    trunk-new-rules-set0/rules/20_phrases.cf
A    trunk-new-rules-set0/rules/20_fake_helo_tests.cf
A    trunk-new-rules-set0/rules/50_scores.cf
A    trunk-new-rules-set0/rules/23_bayes.cf
A    trunk-new-rules-set0/rules/25_uribl.cf
A    trunk-new-rules-set0/rules/init.pre
A    trunk-new-rules-set0/rules/20_vbounce.cf
A    trunk-new-rules-set0/rules/25_textcat.cf
A    trunk-new-rules-set0/rules/10_hasbase.cf
A    trunk-new-rules-set0/rules/sa-update-pubkey.txt
A    trunk-new-rules-set0/rules/60_txrep.cf
A    trunk-new-rules-set0/rules/20_body_tests.cf
A    trunk-new-rules-set0/rules/25_replace.cf
A    trunk-new-rules-set0/rules/20_head_tests.cf
A    trunk-new-rules-set0/rules/20_advance_fee.cf
A    trunk-new-rules-set0/rules/20_freemail.cf
A    trunk-new-rules-set0/rules/20_dnsbl_tests.cf
A    trunk-new-rules-set0/rules/20_html_tests.cf
A    trunk-new-rules-set0/rules/25_asn.cf
A    trunk-new-rules-set0/masses
A    trunk-new-rules-set0/rules/v340.pre
A    trunk-new-rules-set0/rules/local.cf
A    trunk-new-rules-set0/rules/v341.pre
A    trunk-new-rules-set0/rules/v343.pre
A    trunk-new-rules-set0/rules/60_adsp_override_dkim.cf
A    trunk-new-rules-set0/rules/20_net_tests.cf
A    trunk-new-rules-set0/masses/plugins
A    trunk-new-rules-set0/rules/20_aux_tlds.cf
A    trunk-new-rules-set0/rules/20_porn.cf
A    trunk-new-rules-set0/rules/20_uri_tests.cf
A    trunk-new-rules-set0/masses/graphs
A    trunk-new-rules-set0/rules/25_antivirus.cf
A    trunk-new-rules-set0/rules/25_pyzor.cf
A    trunk-new-rules-set0/rules/30_text_pt_br.cf
A    trunk-new-rules-set0/rules/v320.pre
A    trunk-new-rules-set0/rules/20_compensate.cf
A    trunk-new-rules-set0/rules/30_text_nl.cf
A    trunk-new-rules-set0/rules/20_dynrdns.cf
A    trunk-new-rules-set0/rules/20_drugs.cf
A    trunk-new-rules-set0/rules/60_shortcircuit.cf
A    trunk-new-rules-set0/rules/20_imageinfo.cf
A    trunk-new-rules-set0/masses/contrib
A    trunk-new-rules-set0/masses/contrib/automasscheck-minimal
A    trunk-new-rules-set0/rules/STATISTICS-set0.txt
A    trunk-new-rules-set0/rules/STATISTICS-set3.txt
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A    trunk-new-rules-set0/rules/60_whitelist_dkim.cf
A    trunk-new-rules-set0/rules/v330.pre
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A    trunk-new-rules-set0/masses/README.perceptron
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A    trunk-new-rules-set0/masses/plugins/Dumpmem.pm
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A    trunk-new-rules-set0/masses/contrib/automasscheck-minimal/automasscheck-minimal.sh
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A    trunk-new-rules-set0/masses/CORPUS_POLICY
A    trunk-new-rules-set0/masses/contrib/automasscheck-minimal/automasscheck-minimal.cf.dist
A    trunk-new-rules-set0/masses/perceptron.c
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A    trunk-new-rules-set0/masses/rule-update-score-gen/README
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A    trunk-new-rules-set0/masses/contrib/automasscheck-minimal/readme.txt
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A    trunk-new-rules-set0/masses/rule-update-score-gen/do-nightly-rescore-example.sh
A    trunk-new-rules-set0/masses/rule-update-score-gen/masses-Makefile.patch
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A    trunk-new-rules-set0/masses/evolve_metarule/README
A    trunk-new-rules-set0/masses/CORPUS_SUBMIT
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A    trunk-new-rules-set0/rules-base/25_accessdb.cf
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A    trunk-new-rules-set0/rules-base/25_replace.cf
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A    trunk-new-rules-set0/rules-base/60_whitelist_dkim.cf
A    trunk-new-rules-set0/rules-base/25_asn.cf
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A    trunk-new-rules-set0/rules-base/50_scores.cf
A    trunk-new-rules-set0/rules-base/sa-update-pubkey.txt
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A    trunk-new-rules-set0/rules-base/20_uri_tests.cf
A    trunk-new-rules-set0/rules-base/20_drugs.cf
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Checked out revision 1868036.
+ svn co http://svn.apache.org/repos/asf/spamassassin/trunk/rules trunk-new-rules-set0/rules-current
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A    trunk-new-rules-set0/rules-current/60_awl.cf
A    trunk-new-rules-set0/rules-current/20_imageinfo.cf
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A    trunk-new-rules-set0/rules-current/STATISTICS-set3.txt
A    trunk-new-rules-set0/rules-current/25_dnswl.cf
A    trunk-new-rules-set0/rules-current/30_text_de.cf
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A    trunk-new-rules-set0/rules-current/25_dcc.cf
A    trunk-new-rules-set0/rules-current/20_fake_helo_tests.cf
A    trunk-new-rules-set0/rules-current/user_prefs.template
A    trunk-new-rules-set0/rules-current/20_vbounce.cf
A    trunk-new-rules-set0/rules-current/regression_tests.cf
A    trunk-new-rules-set0/rules-current/svn_only.pre
A    trunk-new-rules-set0/rules-current/sa-update-pubkey.txt
A    trunk-new-rules-set0/rules-current/23_bayes.cf
A    trunk-new-rules-set0/rules-current/20_body_tests.cf
A    trunk-new-rules-set0/rules-current/25_textcat.cf
A    trunk-new-rules-set0/rules-current/10_default_prefs.cf
A    trunk-new-rules-set0/rules-current/25_uribl.cf
A    trunk-new-rules-set0/rules-current/20_freemail.cf
A    trunk-new-rules-set0/rules-current/languages
A    trunk-new-rules-set0/rules-current/30_text_pl.cf
A    trunk-new-rules-set0/rules-current/30_text_it.cf
A    trunk-new-rules-set0/rules-current/v310.pre
A    trunk-new-rules-set0/rules-current/25_dkim.cf
A    trunk-new-rules-set0/rules-current/60_whitelist_subject.cf
A    trunk-new-rules-set0/rules-current/10_hasbase.cf
A    trunk-new-rules-set0/rules-current/60_txrep.cf
A    trunk-new-rules-set0/rules-current/25_replace.cf
A    trunk-new-rules-set0/rules-current/25_asn.cf
A    trunk-new-rules-set0/rules-current/20_head_tests.cf
A    trunk-new-rules-set0/rules-current/v320.pre
A    trunk-new-rules-set0/rules-current/20_pdfinfo.cf
A    trunk-new-rules-set0/rules-current/20_html_tests.cf
A    trunk-new-rules-set0/rules-current/25_antivirus.cf
A    trunk-new-rules-set0/rules-current/local.cf
A    trunk-new-rules-set0/rules-current/v340.pre
A    trunk-new-rules-set0/rules-current/v341.pre
A    trunk-new-rules-set0/rules-current/v342.pre
A    trunk-new-rules-set0/rules-current/v343.pre
A    trunk-new-rules-set0/rules-current/60_adsp_override_dkim.cf
A    trunk-new-rules-set0/rules-current/30_text_nl.cf
A    trunk-new-rules-set0/rules-current/20_porn.cf
A    trunk-new-rules-set0/rules-current/20_dynrdns.cf
A    trunk-new-rules-set0/rules-current/20_drugs.cf
A    trunk-new-rules-set0/rules-current/v312.pre
A    trunk-new-rules-set0/rules-current/20_freemail_mailcom_domains.cf
A    trunk-new-rules-set0/rules-current/50_scores.cf
A    trunk-new-rules-set0/rules-current/20_ratware.cf
A    trunk-new-rules-set0/rules-current/20_advance_fee.cf
A    trunk-new-rules-set0/rules-current/20_dnsbl_tests.cf
A    trunk-new-rules-set0/rules-current/20_aux_tlds.cf
A    trunk-new-rules-set0/rules-current/active.list
A    trunk-new-rules-set0/rules-current/30_text_pt_br.cf
A    trunk-new-rules-set0/rules-current/60_whitelist.cf
A    trunk-new-rules-set0/rules-current/60_shortcircuit.cf
A    trunk-new-rules-set0/rules-current/20_compensate.cf
A    trunk-new-rules-set0/rules-current/30_text_fr.cf
A    trunk-new-rules-set0/rules-current/25_razor2.cf
A    trunk-new-rules-set0/rules-current/60_whitelist_spf.cf
A    trunk-new-rules-set0/rules-current/25_accessdb.cf
A    trunk-new-rules-set0/rules-current/20_uri_tests.cf
A    trunk-new-rules-set0/rules-current/25_pyzor.cf
A    trunk-new-rules-set0/rules-current/20_net_tests.cf
A    trunk-new-rules-set0/rules-current/20_mailspike.cf
A    trunk-new-rules-set0/rules-current/60_whitelist_dkim.cf
A    trunk-new-rules-set0/rules-current/v330.pre
A    trunk-new-rules-set0/rules-current/STATISTICS-set2.txt
A    trunk-new-rules-set0/rules-current/STATISTICS-set1.txt
A    trunk-new-rules-set0/rules-current/STATISTICS-set0.txt
 U   trunk-new-rules-set0/rules-current
Checked out revision 1868036.
+ svn up -r 1867965 trunk-new-rules-set0/rulesrc/
Updating 'trunk-new-rules-set0/rulesrc':
At revision 1867965.
+ svn up trunk-new-rules-set0/masses/
Updating 'trunk-new-rules-set0/masses':
At revision 1868036.
+ svn up trunk-new-rules-set0/build/
Updating 'trunk-new-rules-set0/build':
At revision 1868036.
+ cd trunk-new-rules-set0/masses
+ patch
patching file Makefile
+ cp rule-update-score-gen/lock-scores .
+ cp rule-update-score-gen/extract-new-scores .
+ cp rule-update-score-gen/add-hitless-active-to-freqs .
+ cd ..
+ date
Sun Oct  6 02:33:44 UTC 2019
+ echo '[ generating active ruleset via make ]'
+ perl Makefile.PL
[ generating active ruleset via make ]
What email address or URL should be used in the suspected-spam report
text for users who want more information on your filter installation?
(In particular, ISPs should change this to a local Postmaster contact)
default text: [the administrator of that system] the administrator of that system

NOTE: settings for "make test" are now controlled using "t/config.dist". 
See that file if you wish to customize what tests are run, and how.

checking module dependencies and their versions...

***************************************************************************
NOTE: the optional Digest::SHA1 module is not installed.

  The Digest::SHA1 module is still required by the Razor2 plugin.
  Other modules prefer Digest::SHA, which is a Perl base module.


***************************************************************************
NOTE: the optional MaxMind::DB::Reader module is not installed.

  Used by the RelayCountry plugin (not enabled by default) to
  determine the domain country codes of each relay in the path of an email. 
  Also used by the URILocalBL plugin (not enabled by default) to provide ISP
  and Country code based filtering.


***************************************************************************
NOTE: the optional MaxMind::DB::Reader::XS module is not installed.

  Recommended much faster version of the optional MaxMind::DB::Reader module,
  used by RelayCountry / URILocalBL plugins.


***************************************************************************
NOTE: the optional IP::Country::DB_File module is not installed.

  Used by the RelayCountry plugin (not enabled by default) to
  determine the domain country codes of each relay in the path of an email. 
  Also used by the URILocalBL plugin (not enabled by default) to provide
  Country code based filtering.


***************************************************************************
NOTE: the optional BSD::Resource module is not installed.

  BSD::Resource provides BSD process resource limit and priority 
  functions.  It is used by the optional ResourceLimits Plugin.


***************************************************************************
NOTE: the optional Archive::Zip module is not installed.

  Archive::Zip provides an interface to ZIP archive files.
  It is used by the optional OLEMacro Plugin.


***************************************************************************
NOTE: the optional IO::String module is not installed.

  IO::String emulates file interface for in-core strings.
  It is used by the optional OLEMacro Plugin.

checking binary dependencies and their versions...

***************************************************************************
NOTE: the optional fetch binary is not installed.

   Sa-update will use curl, wget or fetch to download updates.  
   Because perl module LWP does not support IPv6, sa-update as of
   3.4.0 will use these standard programs to download rule updates
   leaving LWP as a fallback if none of the programs are found.

   *IMPORTANT NOTE*: You only need one of these programs 
       It's only a concern if you are warned about all 3 
       i.e. (curl, wget & fetch) missing


***************************************************************************
NOTE: the optional re2c binary is not installed.

  The "re2c" program is used by sa-compile to compile rules 
  for regular expressions to speed up scanning.

dependency check complete...

optional module missing: Digest::SHA1
optional module missing: MaxMind::DB::Reader
optional module missing: MaxMind::DB::Reader::XS
optional module missing: IP::Country::DB_File
optional module missing: BSD::Resource
optional module missing: Archive::Zip
optional module missing: IO::String
optional binary missing or nonfunctional: fetch
optional binary missing or nonfunctional: re2c

warning: some functionality may not be available,
please read the above report before continuing!

Checking if your kit is complete...
Looks good
Generating a Unix-style Makefile
Writing Makefile for Mail::SpamAssassin
Writing MYMETA.yml and MYMETA.json
Makefile written by ExtUtils::MakeMaker 7.0401
+ make
+ grep -v '^score' rules/72_active.cf
+ mv -f rules/72_active.cf-scoreless rules/72_active.cf
+ date
Sun Oct  6 02:34:37 UTC 2019
+ echo '[ running log-grep-recent ]'
+ pwd
[ running log-grep-recent ]
/usr/local/spamassassin/automc/tmp/generate-new-scores/trunk-new-rules-set0
+ echo -e '\nmasses/log-grep-recent -m 96 ../corpus/usable-corpus-set0/ham-*.log > masses/ham-full.log'

masses/log-grep-recent -m 96 ../corpus/usable-corpus-set0/ham-*.log > masses/ham-full.log
+ masses/log-grep-recent -m 96 ../corpus/usable-corpus-set0/ham-axb-coi-bulk.r1867965.log ../corpus/usable-corpus-set0/ham-axb-generic.r1867965.log ../corpus/usable-corpus-set0/ham-axb-ham-misc.r1867965.log ../corpus/usable-corpus-set0/ham-darxus.r1867965.log ../corpus/usable-corpus-set0/ham-ena-week3.r1867965.log ../corpus/usable-corpus-set0/ham-ena-week4.r1867965.log ../corpus/usable-corpus-set0/ham-giovanni-ham.r1867965.log ../corpus/usable-corpus-set0/ham-giovanni-spammy.r1867965.log ../corpus/usable-corpus-set0/ham-giovanni-spam.r1867965.log ../corpus/usable-corpus-set0/ham-grenier.r1867965.log ../corpus/usable-corpus-set0/ham-hege.r1867965.log ../corpus/usable-corpus-set0/ham-jarif.r1867965.log ../corpus/usable-corpus-set0/ham-jbrooks.r1867965.log ../corpus/usable-corpus-set0/ham-llanga.r1867965.log ../corpus/usable-corpus-set0/ham-mmiroslaw-mails-ham.r1867965.log ../corpus/usable-corpus-set0/ham-mmiroslaw-mails-spam.r1867965.log ../corpus/usable-corpus-set0/ham-npiazzi.r186796
 5.log ../corpus/usable-corpus-set0/ham-pds.r1867965.log ../corpus/usable-corpus-set0/ham-sihde.r1867965.log ../corpus/usable-corpus-set0/ham-spamsponge.r1867965.log ../corpus/usable-corpus-set0/ham-thendrikx.r1867965.log
Month distribution:

   98496 ( 15%)     98496   0-1 months old
  185940 ( 29%)     87444   1-2 months old
  245972 ( 38%)     60032   2-3 months old
  283617 ( 44%)     37645   3-4 months old
  314209 ( 49%)     30592   4-5 months old
  356880 ( 56%)     42671   5-6 months old
  388942 ( 61%)     32062   6-7 months old
  417570 ( 65%)     28628   7-8 months old
  443501 ( 69%)     25931   8-9 months old
  453542 ( 71%)     10041   9-10 months old
  465552 ( 73%)     12010  10-11 months old
  478854 ( 75%)     13302  11-12 months old
  491854 ( 77%)     13000  12-13 months old
  500477 ( 78%)      8623  13-14 months old
  506899 ( 79%)      6422  14-15 months old
  512290 ( 80%)      5391  15-16 months old
  518422 ( 81%)      6132  16-17 months old
  523003 ( 82%)      4581  17-18 months old
  527604 ( 82%)      4601  18-19 months old
  532080 ( 83%)      4476  19-20 months old
  536587 ( 84%)      4507  20-21 months old
  540548 ( 84%)      3961  21-22 months old
  545369 ( 85%)      4821  22-23 months old
  550026 ( 86%)      4657  23-24 months old
  554004 ( 86%)      3978  24-25 months old
  557706 ( 87%)      3702  25-26 months old
  561623 ( 88%)      3917  26-27 months old
  563902 ( 88%)      2279  27-28 months old
  566600 ( 88%)      2698  28-29 months old
  569662 ( 89%)      3062  29-30 months old
  572666 ( 89%)      3004  30-31 months old
  575455 ( 90%)      2789  31-32 months old
  578468 ( 90%)      3013  32-33 months old
  581087 ( 91%)      2619  33-34 months old
  583859 ( 91%)      2772  34-35 months old
  586407 ( 92%)      2548  35-36 months old
  588841 ( 92%)      2434  36-37 months old
  591257 ( 92%)      2416  37-38 months old
  593644 ( 93%)      2387  38-39 months old
  596562 ( 93%)      2918  39-40 months old
  600020 ( 94%)      3458  40-41 months old
  602361 ( 94%)      2341  41-42 months old
  604696 ( 94%)      2335  42-43 months old
  607552 ( 95%)      2856  43-44 months old
  609868 ( 95%)      2316  44-45 months old
  611209 ( 95%)      1341  45-46 months old
  613253 ( 96%)      2044  46-47 months old
  614935 ( 96%)      1682  47-48 months old
  616432 ( 96%)      1497  48-49 months old
  617734 ( 96%)      1302  49-50 months old
  619131 ( 97%)      1397  50-51 months old
  620056 ( 97%)       925  51-52 months old
  621049 ( 97%)       993  52-53 months old
  622156 ( 97%)      1107  53-54 months old
  623232 ( 97%)      1076  54-55 months old
  624348 ( 97%)      1116  55-56 months old
  625402 ( 98%)      1054  56-57 months old
  626347 ( 98%)       945  57-58 months old
  627245 ( 98%)       898  58-59 months old
  628115 ( 98%)       870  59-60 months old
  629104 ( 98%)       989  60-61 months old
  630014 ( 98%)       910  61-62 months old
  630977 ( 99%)       963  62-63 months old
  631586 ( 99%)       609  63-64 months old
  632069 ( 99%)       483  64-65 months old
  632141 ( 99%)        72  65-66 months old
  632210 ( 99%)        69  66-67 months old
  632284 ( 99%)        74  67-68 months old
  632470 ( 99%)       186  68-69 months old
  632579 ( 99%)       109  69-70 months old
  632823 ( 99%)       244  70-71 months old
  633041 ( 99%)       218  71-72 months old
  633123 ( 99%)        82  72-73 months old
  633228 ( 99%)       105  73-74 months old
  633339 ( 99%)       111  74-75 months old
  633469 ( 99%)       130  75-76 months old
  633551 ( 99%)        82  76-77 months old
  633660 ( 99%)       109  77-78 months old
  633696 ( 99%)        36  78-79 months old
  633728 ( 99%)        32  79-80 months old
  633818 ( 99%)        90  80-81 months old
  633848 ( 99%)        30  81-82 months old
  633894 ( 99%)        46  82-83 months old
  634037 ( 99%)       143  84-85 months old
  634274 ( 99%)       237  85-86 months old
  634496 ( 99%)       222  86-87 months old
  634803 ( 99%)       307  87-88 months old
  635064 ( 99%)       261  88-89 months old
  635235 ( 99%)       171  89-90 months old
  635304 ( 99%)        69  90-91 months old
  635789 ( 99%)       485  91-92 months old
  636335 ( 99%)       546  92-93 months old
  636740 ( 99%)       405  93-94 months old
  637085 ( 99%)       345  94-95 months old
  637088 ( 99%)         3  127-128 months old
  637091 ( 99%)         3  134-135 months old
  637095 (100%)         4  141-142 months old
+ echo -e '\nmasses/log-grep-recent -m 3 ../corpus/usable-corpus-set0/spam-*.log > masses/spam-full.log'

masses/log-grep-recent -m 3 ../corpus/usable-corpus-set0/spam-*.log > masses/spam-full.log
+ masses/log-grep-recent -m 3 ../corpus/usable-corpus-set0/spam-axb-coi-bulk.r1867965.log ../corpus/usable-corpus-set0/spam-axb-generic.r1867965.log ../corpus/usable-corpus-set0/spam-axb-ham-misc.r1867965.log ../corpus/usable-corpus-set0/spam-darxus.r1867965.log ../corpus/usable-corpus-set0/spam-ena-week3.r1867965.log ../corpus/usable-corpus-set0/spam-ena-week4.r1867965.log ../corpus/usable-corpus-set0/spam-giovanni-ham.r1867965.log ../corpus/usable-corpus-set0/spam-giovanni-spammy.r1867965.log ../corpus/usable-corpus-set0/spam-giovanni-spam.r1867965.log ../corpus/usable-corpus-set0/spam-grenier.r1867965.log ../corpus/usable-corpus-set0/spam-hege.r1867965.log ../corpus/usable-corpus-set0/spam-jarif.r1867965.log ../corpus/usable-corpus-set0/spam-jbrooks.r1867965.log ../corpus/usable-corpus-set0/spam-llanga.r1867965.log ../corpus/usable-corpus-set0/spam-mmiroslaw-mails-ham.r1867965.log ../corpus/usable-corpus-set0/spam-mmiroslaw-mails-spam.r1867965.log ../corpus/usable-corpus-set0/spam
 -npiazzi.r1867965.log ../corpus/usable-corpus-set0/spam-pds.r1867965.log ../corpus/usable-corpus-set0/spam-sihde.r1867965.log ../corpus/usable-corpus-set0/spam-spamsponge.r1867965.log ../corpus/usable-corpus-set0/spam-thendrikx.r1867965.log
Month distribution:

  484756 ( 64%)    484756   0-1 months old
  670240 ( 89%)    185484   1-2 months old
  672970 ( 90%)      2730   2-3 months old
  674904 ( 90%)      1934   3-4 months old
  677241 ( 90%)      2337   4-5 months old
  679932 ( 91%)      2691   5-6 months old
  681573 ( 91%)      1641   6-7 months old
  699570 ( 93%)     17997   7-8 months old
  701141 ( 93%)      1571   8-9 months old
  702405 ( 94%)      1264   9-10 months old
  703349 ( 94%)       944  10-11 months old
  704228 ( 94%)       879  11-12 months old
  705448 ( 94%)      1220  12-13 months old
  706880 ( 94%)      1432  13-14 months old
  708291 ( 94%)      1411  14-15 months old
  709656 ( 95%)      1365  15-16 months old
  711067 ( 95%)      1411  16-17 months old
  712398 ( 95%)      1331  17-18 months old
  713336 ( 95%)       938  18-19 months old
  714096 ( 95%)       760  19-20 months old
  714889 ( 95%)       793  20-21 months old
  715661 ( 95%)       772  21-22 months old
  716734 ( 95%)      1073  22-23 months old
  717652 ( 96%)       918  23-24 months old
  718477 ( 96%)       825  24-25 months old
  719069 ( 96%)       592  25-26 months old
  719595 ( 96%)       526  26-27 months old
  720202 ( 96%)       607  27-28 months old
  720745 ( 96%)       543  28-29 months old
  721241 ( 96%)       496  29-30 months old
  721785 ( 96%)       544  30-31 months old
  722418 ( 96%)       633  31-32 months old
  723003 ( 96%)       585  32-33 months old
  723435 ( 96%)       432  33-34 months old
  724084 ( 96%)       649  34-35 months old
  724659 ( 97%)       575  35-36 months old
  725405 ( 97%)       746  36-37 months old
  726102 ( 97%)       697  37-38 months old
  726669 ( 97%)       567  38-39 months old
  727308 ( 97%)       639  39-40 months old
  727957 ( 97%)       649  40-41 months old
  728606 ( 97%)       649  41-42 months old
  729215 ( 97%)       609  42-43 months old
  729893 ( 97%)       678  43-44 months old
  730669 ( 97%)       776  44-45 months old
  731344 ( 97%)       675  45-46 months old
  732266 ( 98%)       922  46-47 months old
  733199 ( 98%)       933  47-48 months old
  734190 ( 98%)       991  48-49 months old
  735113 ( 98%)       923  49-50 months old
  736037 ( 98%)       924  50-51 months old
  737096 ( 98%)      1059  51-52 months old
  737998 ( 98%)       902  52-53 months old
  738772 ( 98%)       774  53-54 months old
  739593 ( 99%)       821  54-55 months old
  740529 ( 99%)       936  55-56 months old
  741774 ( 99%)      1245  56-57 months old
  742751 ( 99%)       977  57-58 months old
  743757 ( 99%)      1006  58-59 months old
  744683 ( 99%)       926  59-60 months old
  745490 ( 99%)       807  60-61 months old
  745637 ( 99%)       147  61-62 months old
  745819 ( 99%)       182  62-63 months old
  745970 ( 99%)       151  63-64 months old
  746021 ( 99%)        51  64-65 months old
  746095 ( 99%)        74  65-66 months old
  746212 ( 99%)       117  66-67 months old
  746369 ( 99%)       157  67-68 months old
  746512 ( 99%)       143  68-69 months old
  746609 ( 99%)        97  69-70 months old
  746615 ( 99%)         6  70-71 months old
  746618 ( 99%)         3  77-78 months old
  746619 ( 99%)         1  78-79 months old
  746620 ( 99%)         1  79-80 months old
  746621 ( 99%)         1  81-82 months old
  746622 ( 99%)         1  82-83 months old
  746624 (100%)         2  83-84 months old
++ wc -l masses/ham-full.log
++ sed -e 's/^[ \t]*//'
++ cut '-d ' -f1
+ HAMCOUNT=637085
++ wc -l masses/spam-full.log
++ sed -e 's/^[ \t]*//'
++ cut '-d ' -f1
+ SPAMCOUNT=674904
+ echo ' HAM: 637085 (100000 required)'
+ echo 'SPAM: 674904 (100000 required)'
 HAM: 637085 (100000 required)
SPAM: 674904 (100000 required)
+ [[ 637085 -lt 100000 ]]
+ [[ 674904 -lt 100000 ]]
+ cp masses/config.set0 masses/config
+ . masses/config
++ SCORESET=0
++ HAM_PREFERENCE=5
++ THRESHOLD=5.0
++ EPOCHS=6000
++ NOTE=
+ NAME=set0
+ LOGDIR=gen-set0-5-5.0-6000-ga
+ date
Sun Oct  6 02:43:20 UTC 2019
+ echo '[ running make freqs ]'
+ cd masses
[ running make freqs ]
+ pwd
+ set -x
/usr/local/spamassassin/automc/tmp/generate-new-scores/trunk-new-rules-set0/masses
+ make clean
rm -rf *.o perceptron tmp freqs badrules \
          perceptron.scores garescorer garescorer.scores
+ set +x
+ make freqs SCORESET=0
perl hit-frequencies -c ../rules -x -p -s 0 > freqs
+ make
+ set +x
Sun Oct  6 03:01:18 UTC 2019
[ starting runGA ]
+ mkdir -p gen-set0-5-5.0-6000-ga gen-set0-5-5.0-6000-ga/NSBASE gen-set0-5-5.0-6000-ga/SPBASE
tee: gen-set0-5-5.0-6000-ga/log: No such file or directory
+ [ -d gen-set0-5-5.0-6000-ga ]
+ rm -rf tmprules
+ cp -r ../rules tmprules
+ cp tmprules/50_scores.cf orig_scores.cf
+ ./enable-all-evolved-rules
Argument "2015-05-01" isn't numeric in addition (+) at ./enable-all-evolved-rules line 47, <> line 345.
+ mv tmprules/50_scores.cf.new tmprules/50_scores.cf
+ [ y = y ]
+ rm tmprules/70_sandbox.cf
+ echo [Doing a scoreset 0 score-generation run]
+ echo [Cleaning up]
+ rm -rf spam-test.log ham-test.log spam.log ham.log NSBASE SPBASE tmp make.output[Doing a scoreset 0 score-generation run]
[Cleaning up]
 freqs perceptron.scores garescorer.scores
+ make clean
rm -rf *.o perceptron tmp freqs badrules \
          perceptron.scores garescorer garescorer.scores
+ echo [Generating 90/10 split ham]
+ perl tenpass/split-log-into-buckets-cached 9:gen-cache/ham-split9.log 1:gen-cache/ham-split1.log ORIG/ham-set0.log
[Generating 90/10 split ham]
Creating gen-cache/ham-split9.log with 9 buckets
Creating gen-cache/ham-split1.log with 1 buckets
Reading from ORIG/ham-set0.log
+ ln gen-cache/ham-split9.log gen-set0-5-5.0-6000-ga/NSBASE/ham.log
+ ln gen-cache/ham-split1.log gen-set0-5-5.0-6000-ga/NSBASE/ham-test.log
+ echo [Generating 90/10 split spam]
+ perl tenpass/split-log-into-buckets-cached 9:gen-cache/spam-split9.log 1:gen-cache/spam-split1.log ORIG/spam-set0.log
[Generating 90/10 split spam]
Creating gen-cache/spam-split9.log with 9 buckets
Creating gen-cache/spam-split1.log with 1 buckets
Reading from ORIG/spam-set0.log
+ ln gen-cache/spam-split9.log gen-set0-5-5.0-6000-ga/SPBASE/spam.log
+ ln gen-cache/spam-split1.log gen-set0-5-5.0-6000-ga/SPBASE/spam-test.log
+ echo [Setting up for gen run]
+ ln -s gen-set0-5-5.0-6000-ga/SPBASE/spam.log .
[Setting up for gen run]
+ ln -s gen-set0-5-5.0-6000-ga/NSBASE/ham.log .
+ ln -s gen-set0-5-5.0-6000-ga/SPBASE/spam-test.log .
+ ln -s gen-set0-5-5.0-6000-ga/NSBASE/ham-test.log .
+ uname
+ ostype=Linux
+ [ Linux = FreeBSD ]
+ [ Linux = SunOS ]
+ cpucount
+ egrep -c ^processor\b /proc/cpuinfo
+ numcpus=6
+ [ 6 -le 0 ]
+ echo [Generating GA]
[Generating GA]
+ make -j 6 SCORESET=0 garescorer
+ cp freqs gen-set0-5-5.0-6000-ga/freqs
+ echo [config]
+ cat config
[config]
SCORESET=0
HAM_PREFERENCE=5
THRESHOLD=5.0
EPOCHS=6000
NOTE=
+ echo [gen run start]
+ pwd
[gen run start]
+ date/usr/local/spamassassin/automc/tmp/generate-new-scores/trunk-new-rules-set0/masses

Sun Oct  6 03:17:28 UTC 2019
+ time ./garescorer -b 5 -e 6000 -t 5.0
Read test results for 42663 messages (1049556 total).
Read scores for 604 tests.
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 15.393 iterations/s, iteration no. 50

# SUMMARY for threshold 5.0:
# Correctly non-spam: 508004  48.402%  (99.667% of non-spam corpus)
# Correctly spam:     384928  36.675%  (71.302% of spam corpus)
# False positives:      1695  0.161%  (0.333% of nonspam,  54413 weighted)
# False negatives:    154929  14.761%  (28.698% of spam, 394077 weighted)
# Average score for spam:  9.7    nonspam: 0.5
# Average for false-pos:   6.1  false-neg: 2.5
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.553 iterations/s, iteration no. 100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507985  48.400%  (99.664% of non-spam corpus)
# Correctly spam:     400398  38.149%  (74.167% of spam corpus)
# False positives:      1714  0.163%  (0.336% of nonspam,  55057 weighted)
# False negatives:    139459  13.287%  (25.833% of spam, 333694 weighted)
# Average score for spam:  9.9    nonspam: 0.5
# Average for false-pos:   6.1  false-neg: 2.4
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.964 iterations/s, iteration no. 150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507863  48.388%  (99.640% of non-spam corpus)
# Correctly spam:     405996  38.683%  (75.204% of spam corpus)
# False positives:      1836  0.175%  (0.360% of nonspam,  59600 weighted)
# False negatives:    133861  12.754%  (24.796% of spam, 316399 weighted)
# Average score for spam:  10.2    nonspam: 0.6
# Average for false-pos:   6.1  false-neg: 2.4
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.043 iterations/s, iteration no. 200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507786  48.381%  (99.625% of non-spam corpus)
# Correctly spam:     408212  38.894%  (75.615% of spam corpus)
# False positives:      1913  0.182%  (0.375% of nonspam,  60468 weighted)
# False negatives:    131645  12.543%  (24.385% of spam, 309916 weighted)
# Average score for spam:  10.4    nonspam: 0.6
# Average for false-pos:   6.0  false-neg: 2.4
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 11.948 iterations/s, iteration no. 250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507632  48.366%  (99.594% of non-spam corpus)
# Correctly spam:     410321  39.095%  (76.006% of spam corpus)
# False positives:      2067  0.197%  (0.406% of nonspam,  65167 weighted)
# False negatives:    129536  12.342%  (23.995% of spam, 302699 weighted)
# Average score for spam:  10.6    nonspam: 0.6
# Average for false-pos:   6.0  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.066 iterations/s, iteration no. 300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507614  48.365%  (99.591% of non-spam corpus)
# Correctly spam:     410922  39.152%  (76.117% of spam corpus)
# False positives:      2085  0.199%  (0.409% of nonspam,  65684 weighted)
# False negatives:    128935  12.285%  (23.883% of spam, 301823 weighted)
# Average score for spam:  10.8    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
300        Best       3.533110e+05
           Average    3.533888e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.767 iterations/s, iteration no. 350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507668  48.370%  (99.602% of non-spam corpus)
# Correctly spam:     411832  39.239%  (76.285% of spam corpus)
# False positives:      2031  0.194%  (0.398% of nonspam,  63978 weighted)
# False negatives:    128025  12.198%  (23.715% of spam, 298439 weighted)
# Average score for spam:  10.9    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 11.618 iterations/s, iteration no. 400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507624  48.366%  (99.593% of non-spam corpus)
# Correctly spam:     411953  39.250%  (76.308% of spam corpus)
# False positives:      2075  0.198%  (0.407% of nonspam,  65260 weighted)
# False negatives:    127904  12.186%  (23.692% of spam, 298638 weighted)
# Average score for spam:  11.0    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.839 iterations/s, iteration no. 450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507611  48.364%  (99.590% of non-spam corpus)
# Correctly spam:     412123  39.266%  (76.339% of spam corpus)
# False positives:      2088  0.199%  (0.410% of nonspam,  65668 weighted)
# False negatives:    127734  12.170%  (23.661% of spam, 298449 weighted)
# Average score for spam:  11.1    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 11.565 iterations/s, iteration no. 500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507600  48.363%  (99.588% of non-spam corpus)
# Correctly spam:     411870  39.242%  (76.292% of spam corpus)
# False positives:      2099  0.200%  (0.412% of nonspam,  65939 weighted)
# False negatives:    127987  12.194%  (23.708% of spam, 300092 weighted)
# Average score for spam:  11.1    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.119 iterations/s, iteration no. 550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507598  48.363%  (99.588% of non-spam corpus)
# Correctly spam:     411984  39.253%  (76.314% of spam corpus)
# False positives:      2101  0.200%  (0.412% of nonspam,  66030 weighted)
# False negatives:    127873  12.184%  (23.686% of spam, 299846 weighted)
# Average score for spam:  11.2    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.453 iterations/s, iteration no. 600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507593  48.363%  (99.587% of non-spam corpus)
# Correctly spam:     412363  39.289%  (76.384% of spam corpus)
# False positives:      2106  0.201%  (0.413% of nonspam,  66105 weighted)
# False negatives:    127494  12.147%  (23.616% of spam, 298116 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
600        Best       3.496944e+05
           Average    3.497531e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 15.578 iterations/s, iteration no. 650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507594  48.363%  (99.587% of non-spam corpus)
# Correctly spam:     411908  39.246%  (76.299% of spam corpus)
# False positives:      2105  0.201%  (0.413% of nonspam,  66125 weighted)
# False negatives:    127949  12.191%  (23.701% of spam, 300548 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.892 iterations/s, iteration no. 700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412425  39.295%  (76.395% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66224 weighted)
# False negatives:    127432  12.142%  (23.605% of spam, 298043 weighted)
# Average score for spam:  11.2    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.926 iterations/s, iteration no. 750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412478  39.300%  (76.405% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66293 weighted)
# False negatives:    127379  12.136%  (23.595% of spam, 297856 weighted)
# Average score for spam:  11.2    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.393 iterations/s, iteration no. 800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412044  39.259%  (76.325% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66224 weighted)
# False negatives:    127813  12.178%  (23.675% of spam, 300047 weighted)
# Average score for spam:  11.2    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.585 iterations/s, iteration no. 850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507591  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412494  39.302%  (76.408% of spam corpus)
# False positives:      2108  0.201%  (0.414% of nonspam,  66192 weighted)
# False negatives:    127363  12.135%  (23.592% of spam, 297849 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.020 iterations/s, iteration no. 900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507584  48.362%  (99.585% of non-spam corpus)
# Correctly spam:     412499  39.302%  (76.409% of spam corpus)
# False positives:      2115  0.202%  (0.415% of nonspam,  66381 weighted)
# False negatives:    127358  12.134%  (23.591% of spam, 297856 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
900        Best       3.493115e+05
           Average    3.493799e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.793 iterations/s, iteration no. 950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507585  48.362%  (99.585% of non-spam corpus)
# Correctly spam:     412511  39.303%  (76.411% of spam corpus)
# False positives:      2114  0.201%  (0.415% of nonspam,  66351 weighted)
# False negatives:    127346  12.133%  (23.589% of spam, 297799 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.260 iterations/s, iteration no. 1000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412096  39.264%  (76.334% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66276 weighted)
# False negatives:    127761  12.173%  (23.666% of spam, 299892 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.666 iterations/s, iteration no. 1050

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507586  48.362%  (99.585% of non-spam corpus)
# Correctly spam:     412110  39.265%  (76.337% of spam corpus)
# False positives:      2113  0.201%  (0.415% of nonspam,  66378 weighted)
# False negatives:    127747  12.172%  (23.663% of spam, 299881 weighted)
# Average score for spam:  11.3    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.969 iterations/s, iteration no. 1100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412121  39.266%  (76.339% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66346 weighted)
# False negatives:    127736  12.170%  (23.661% of spam, 299827 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.350 iterations/s, iteration no. 1150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412123  39.266%  (76.339% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66371 weighted)
# False negatives:    127734  12.170%  (23.661% of spam, 299845 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 15.397 iterations/s, iteration no. 1200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412106  39.265%  (76.336% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66286 weighted)
# False negatives:    127751  12.172%  (23.664% of spam, 299927 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
1200       Best       3.492689e+05
           Average    3.492949e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.626 iterations/s, iteration no. 1250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412118  39.266%  (76.338% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66321 weighted)
# False negatives:    127739  12.171%  (23.662% of spam, 299877 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.909 iterations/s, iteration no. 1300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412118  39.266%  (76.338% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66323 weighted)
# False negatives:    127739  12.171%  (23.662% of spam, 299880 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.443 iterations/s, iteration no. 1350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412110  39.265%  (76.337% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66323 weighted)
# False negatives:    127747  12.172%  (23.663% of spam, 299920 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.021 iterations/s, iteration no. 1400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412110  39.265%  (76.337% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66348 weighted)
# False negatives:    127747  12.172%  (23.663% of spam, 299919 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 12.537 iterations/s, iteration no. 1450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412110  39.265%  (76.337% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66348 weighted)
# False negatives:    127747  12.172%  (23.663% of spam, 299920 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 15.937 iterations/s, iteration no. 1500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412107  39.265%  (76.336% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66344 weighted)
# False negatives:    127750  12.172%  (23.664% of spam, 299931 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
1500       Best       3.492649e+05
           Average    3.493071e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.987 iterations/s, iteration no. 1550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412118  39.266%  (76.338% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66348 weighted)
# False negatives:    127739  12.171%  (23.662% of spam, 299881 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.331 iterations/s, iteration no. 1600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412113  39.265%  (76.337% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66322 weighted)
# False negatives:    127744  12.171%  (23.663% of spam, 299906 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.314 iterations/s, iteration no. 1650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66323 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299904 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.323 iterations/s, iteration no. 1700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66323 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299906 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.330 iterations/s, iteration no. 1750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507589  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412115  39.266%  (76.338% of spam corpus)
# False positives:      2110  0.201%  (0.414% of nonspam,  66324 weighted)
# False negatives:    127742  12.171%  (23.662% of spam, 299902 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 14.431 iterations/s, iteration no. 1800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412115  39.266%  (76.338% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66351 weighted)
# False negatives:    127742  12.171%  (23.662% of spam, 299902 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
1800       Best       3.492607e+05
           Average    3.494751e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.921 iterations/s, iteration no. 1850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507588  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412104  39.265%  (76.336% of spam corpus)
# False positives:      2111  0.201%  (0.414% of nonspam,  66348 weighted)
# False negatives:    127753  12.172%  (23.664% of spam, 299955 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.953 iterations/s, iteration no. 1900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507586  48.362%  (99.585% of non-spam corpus)
# Correctly spam:     412024  39.257%  (76.321% of spam corpus)
# False positives:      2113  0.201%  (0.415% of nonspam,  66402 weighted)
# False negatives:    127833  12.180%  (23.679% of spam, 300356 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 0 0 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 13.617 iterations/s, iteration no. 1950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412117  39.266%  (76.338% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66374 weighted)
# False negatives:    127740  12.171%  (23.662% of spam, 299892 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 607 325 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 9.870 iterations/s, iteration no. 2000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412119  39.266%  (76.339% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66376 weighted)
# False negatives:    127738  12.171%  (23.661% of spam, 299884 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1394 749 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.430 iterations/s, iteration no. 2050

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507586  48.362%  (99.585% of non-spam corpus)
# Correctly spam:     412130  39.267%  (76.341% of spam corpus)
# False positives:      2113  0.201%  (0.415% of nonspam,  66404 weighted)
# False negatives:    127727  12.170%  (23.659% of spam, 299830 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1378 735 0 0 0
Adapt (over, cross, repeat): 0 6 0
Performance: 7.321 iterations/s, iteration no. 2100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412130  39.267%  (76.341% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66377 weighted)
# False negatives:    127727  12.170%  (23.659% of spam, 299830 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
2100       Best       3.492577e+05
           Average    3.493167e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1298 693 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 7.608 iterations/s, iteration no. 2150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412130  39.267%  (76.341% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66377 weighted)
# False negatives:    127727  12.170%  (23.659% of spam, 299830 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1330 717 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 7.920 iterations/s, iteration no. 2200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412130  39.267%  (76.341% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66377 weighted)
# False negatives:    127727  12.170%  (23.659% of spam, 299830 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1335 721 0 0 0
Adapt (over, cross, repeat): 0 13 0
Performance: 8.163 iterations/s, iteration no. 2250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412119  39.266%  (76.339% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66375 weighted)
# False negatives:    127738  12.171%  (23.661% of spam, 299884 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1301 708 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.501 iterations/s, iteration no. 2300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507587  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412118  39.266%  (76.338% of spam corpus)
# False positives:      2112  0.201%  (0.414% of nonspam,  66375 weighted)
# False negatives:    127739  12.171%  (23.662% of spam, 299889 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1318 714 0 0 0
Adapt (over, cross, repeat): 0 5 0
Performance: 7.554 iterations/s, iteration no. 2350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507577  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2122  0.202%  (0.416% of nonspam,  66641 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299910 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1351 736 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 7.855 iterations/s, iteration no. 2400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507577  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2122  0.202%  (0.416% of nonspam,  66641 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299910 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
2400       Best       3.492570e+05
           Average    3.492967e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1295 704 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.288 iterations/s, iteration no. 2450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507577  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2122  0.202%  (0.416% of nonspam,  66641 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299910 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1347 732 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.603 iterations/s, iteration no. 2500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507577  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2122  0.202%  (0.416% of nonspam,  66641 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299910 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1394 760 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 7.590 iterations/s, iteration no. 2550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507577  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2122  0.202%  (0.416% of nonspam,  66641 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299910 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1293 703 0 0 0
Adapt (over, cross, repeat): 0 6 0
Performance: 7.944 iterations/s, iteration no. 2600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507579  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412114  39.266%  (76.338% of spam corpus)
# False positives:      2120  0.202%  (0.416% of nonspam,  66587 weighted)
# False negatives:    127743  12.171%  (23.662% of spam, 299911 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1312 705 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 8.299 iterations/s, iteration no. 2650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507579  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2120  0.202%  (0.416% of nonspam,  66587 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299921 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1218 660 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.981 iterations/s, iteration no. 2700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66561 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299921 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
2700       Best       3.492551e+05
           Average    3.492966e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1261 678 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 7.909 iterations/s, iteration no. 2750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66561 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299921 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1205 658 0 0 0
Adapt (over, cross, repeat): 0 6 0
Performance: 8.588 iterations/s, iteration no. 2800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66561 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299927 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1333 720 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 7.551 iterations/s, iteration no. 2850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66561 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299927 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1298 718 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.030 iterations/s, iteration no. 2900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66561 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299927 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1265 695 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 8.646 iterations/s, iteration no. 2950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66965 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299930 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1259 690 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 7.911 iterations/s, iteration no. 3000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66965 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299935 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
3000       Best       3.492537e+05
           Average    3.493476e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1355 742 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 8.307 iterations/s, iteration no. 3050

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66965 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299936 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1223 679 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 9.037 iterations/s, iteration no. 3100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66965 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299936 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1249 686 0 0 0
Adapt (over, cross, repeat): 0 7 0
Performance: 8.210 iterations/s, iteration no. 3150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66965 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299933 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1274 696 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.867 iterations/s, iteration no. 3200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66966 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299934 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1322 723 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 7.888 iterations/s, iteration no. 3250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66966 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299934 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1263 698 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 8.492 iterations/s, iteration no. 3300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66966 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299934 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
3300       Best       3.492499e+05
           Average    3.492849e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1234 685 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 7.845 iterations/s, iteration no. 3350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412112  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66966 weighted)
# False negatives:    127745  12.171%  (23.663% of spam, 299934 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1240 679 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 8.515 iterations/s, iteration no. 3400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412111  39.265%  (76.337% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66966 weighted)
# False negatives:    127746  12.171%  (23.663% of spam, 299939 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1259 697 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 7.821 iterations/s, iteration no. 3450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507565  48.360%  (99.581% of non-spam corpus)
# Correctly spam:     412091  39.263%  (76.333% of spam corpus)
# False positives:      2134  0.203%  (0.419% of nonspam,  66970 weighted)
# False negatives:    127766  12.173%  (23.667% of spam, 300043 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1159 648 0 0 0
Adapt (over, cross, repeat): 0 6 0
Performance: 8.671 iterations/s, iteration no. 3500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507579  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412089  39.263%  (76.333% of spam corpus)
# False positives:      2120  0.202%  (0.416% of nonspam,  66598 weighted)
# False negatives:    127768  12.174%  (23.667% of spam, 300053 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1311 733 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 7.911 iterations/s, iteration no. 3550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412089  39.263%  (76.333% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127768  12.174%  (23.667% of spam, 300052 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1223 678 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.650 iterations/s, iteration no. 3600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412089  39.263%  (76.333% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127768  12.174%  (23.667% of spam, 300052 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
3600       Best       3.492495e+05
           Average    3.492979e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1290 715 0 0 0
Adapt (over, cross, repeat): 0 5 0
Performance: 7.831 iterations/s, iteration no. 3650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412089  39.263%  (76.333% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127768  12.174%  (23.667% of spam, 300052 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1200 663 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.599 iterations/s, iteration no. 3700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412089  39.263%  (76.333% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127768  12.174%  (23.667% of spam, 300052 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1286 722 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 7.894 iterations/s, iteration no. 3750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300077 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1239 687 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.575 iterations/s, iteration no. 3800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507580  48.361%  (99.584% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2119  0.202%  (0.416% of nonspam,  66571 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300077 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1288 707 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 7.782 iterations/s, iteration no. 3850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412083  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66306 weighted)
# False negatives:    127774  12.174%  (23.668% of spam, 300082 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1279 712 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.405 iterations/s, iteration no. 3900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412083  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66306 weighted)
# False negatives:    127774  12.174%  (23.668% of spam, 300084 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
3900       Best       3.492476e+05
           Average    3.492918e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1219 679 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 7.810 iterations/s, iteration no. 3950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1291 723 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.497 iterations/s, iteration no. 4000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1272 704 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 7.776 iterations/s, iteration no. 4050

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1321 732 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.337 iterations/s, iteration no. 4100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1235 690 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 9.219 iterations/s, iteration no. 4150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1255 708 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.542 iterations/s, iteration no. 4200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
4200       Best       3.492476e+05
           Average    3.493148e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1266 709 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 7.940 iterations/s, iteration no. 4250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1257 710 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.690 iterations/s, iteration no. 4300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.6    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1226 703 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.217 iterations/s, iteration no. 4350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1274 717 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.993 iterations/s, iteration no. 4400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1286 727 0 0 0
Adapt (over, cross, repeat): 0 5 0
Performance: 8.331 iterations/s, iteration no. 4450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1221 698 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 9.317 iterations/s, iteration no. 4500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
4500       Best       3.492476e+05
           Average    3.493081e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1207 681 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.741 iterations/s, iteration no. 4550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507590  48.362%  (99.586% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2109  0.201%  (0.414% of nonspam,  66307 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300080 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.9  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1223 691 0 0 0
Adapt (over, cross, repeat): 0 6 0
Performance: 8.175 iterations/s, iteration no. 4600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300082 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1235 685 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.979 iterations/s, iteration no. 4650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300082 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1347 753 0 0 0
Adapt (over, cross, repeat): 0 7 0
Performance: 8.134 iterations/s, iteration no. 4700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78064 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300082 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1252 699 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.916 iterations/s, iteration no. 4750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78064 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300082 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1184 678 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 8.439 iterations/s, iteration no. 4800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412084  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127773  12.174%  (23.668% of spam, 300084 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
4800       Best       3.492452e+05
           Average    3.493292e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1272 716 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 7.905 iterations/s, iteration no. 4850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1222 688 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.717 iterations/s, iteration no. 4900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1309 733 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 7.999 iterations/s, iteration no. 4950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1294 732 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.784 iterations/s, iteration no. 5000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1214 694 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.315 iterations/s, iteration no. 5050

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300079 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1254 714 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 9.098 iterations/s, iteration no. 5100

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412085  39.263%  (76.332% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127772  12.174%  (23.668% of spam, 300078 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
5100       Best       3.492452e+05
           Average    3.493188e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1182 681 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.663 iterations/s, iteration no. 5150

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507146  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412091  39.263%  (76.333% of spam corpus)
# False positives:      2553  0.243%  (0.501% of nonspam,  78065 weighted)
# False negatives:    127766  12.173%  (23.667% of spam, 300048 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1291 737 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 8.035 iterations/s, iteration no. 5200

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412093  39.264%  (76.334% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127764  12.173%  (23.666% of spam, 300038 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1236 709 0 0 0
Adapt (over, cross, repeat): 0 4 0
Performance: 8.952 iterations/s, iteration no. 5250

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412093  39.264%  (76.334% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127764  12.173%  (23.666% of spam, 300038 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1227 700 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.346 iterations/s, iteration no. 5300

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412104  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127753  12.172%  (23.664% of spam, 299984 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1285 741 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 9.185 iterations/s, iteration no. 5350

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412104  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127753  12.172%  (23.664% of spam, 299984 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1250 721 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.618 iterations/s, iteration no. 5400

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412104  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127753  12.172%  (23.664% of spam, 299984 weighted)
# Average score for spam:  11.4    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
5400       Best       3.492452e+05
           Average    3.493585e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1195 682 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 8.129 iterations/s, iteration no. 5450

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1232 708 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 9.134 iterations/s, iteration no. 5500

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1254 721 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.470 iterations/s, iteration no. 5550

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1300 743 0 0 0
Adapt (over, cross, repeat): 0 0 0
Performance: 7.795 iterations/s, iteration no. 5600

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1258 712 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.566 iterations/s, iteration no. 5650

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1156 658 0 0 0
Adapt (over, cross, repeat): 0 1 0
Performance: 8.147 iterations/s, iteration no. 5700

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

Iter #     Field      Value
5700       Best       3.492449e+05
           Average    3.492984e+05
123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1198 699 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 9.220 iterations/s, iteration no. 5750

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78118 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1255 726 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.644 iterations/s, iteration no. 5800

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78119 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1219 715 0 0 0
Adapt (over, cross, repeat): 0 3 0
Performance: 8.192 iterations/s, iteration no. 5850

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     412103  39.265%  (76.336% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78119 weighted)
# False negatives:    127754  12.172%  (23.664% of spam, 299989 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.3
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1261 728 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 9.159 iterations/s, iteration no. 5900

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507144  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     411693  39.225%  (76.260% of spam corpus)
# False positives:      2555  0.243%  (0.501% of nonspam,  78119 weighted)
# False negatives:    128164  12.211%  (23.740% of spam, 302039 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.4
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1204 696 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.675 iterations/s, iteration no. 5950

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507143  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     411696  39.226%  (76.260% of spam corpus)
# False positives:      2556  0.244%  (0.501% of nonspam,  78148 weighted)
# False negatives:    128161  12.211%  (23.740% of spam, 302029 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.4
# TOTAL:              1049556  100.00%

123456789
Pop size, replacement: 50 33

Adapt (t, fneg, fneg_add, fpos, fpos_add): 1210 708 0 0 0
Adapt (over, cross, repeat): 0 2 0
Performance: 8.200 iterations/s, iteration no. 6000

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507143  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     411701  39.226%  (76.261% of spam corpus)
# False positives:      2556  0.244%  (0.501% of nonspam,  78148 weighted)
# False negatives:    128156  12.210%  (23.739% of spam, 302004 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.4
# TOTAL:              1049556  100.00%

Iter #     Field      Value
6000       Best       3.492437e+05
           Average    3.492704e+05
The Best Evaluation: 3.492437e+05.
The Best String:

# SUMMARY for threshold 5.0:
# Correctly non-spam: 507143  48.320%  (99.499% of non-spam corpus)
# Correctly spam:     411701  39.226%  (76.261% of spam corpus)
# False positives:      2556  0.244%  (0.501% of nonspam,  78148 weighted)
# False negatives:    128156  12.210%  (23.739% of spam, 302004 weighted)
# Average score for spam:  11.5    nonspam: 0.6
# Average for false-pos:   5.8  false-neg: 2.4
# TOTAL:              1049556  100.00%

score AC_BR_BONANZA                  0.001
score AC_DIV_BONANZA                 0.001
score AC_FROM_MANY_DOTS              2.999
score ADMITS_SPAM                    3.199
score ADVANCE_FEE_2_NEW_MONEY        1.999
score ADVANCE_FEE_3_NEW              2.601
score ADVANCE_FEE_3_NEW_FORM         1.632
score ADVANCE_FEE_3_NEW_FRM_MNY      1.436
score ADVANCE_FEE_3_NEW_MONEY        2.046
score ADVANCE_FEE_4_NEW              2.799
score ADVANCE_FEE_4_NEW_MONEY        2.202
score ADVANCE_FEE_5_NEW              1.396
score ADVANCE_FEE_5_NEW_FRM_MNY      0.001
score ADVANCE_FEE_5_NEW_MONEY        0.006
score AD_PREFS                       0.499
score ALIBABA_IMG_NOT_RCVD_ALI       2.499
score AMAZON_IMG_NOT_RCVD_AMZN       2.249
score ANY_PILL_PRICE                 2.000
score AXB_XMAILER_MIMEOLE_OL_024C2   4.399
score AXB_X_AOL_SEZ_S                2.499
score BITCOIN_EXTORT_01              2.502
score BITCOIN_PAY_ME                 2.999
score BITCOIN_SPAM_01                0.196
score BITCOIN_SPAM_02                2.499
score BITCOIN_SPAM_04                1.499
score BITCOIN_SPAM_06                0.001
score BITCOIN_SPAM_07                3.499
score BITCOIN_SPAM_08                0.247
score BITCOIN_SPAM_09                1.499
score BODY_EMPTY                     1.999
score BODY_URI_ONLY                  0.999
score BOGUS_MIME_VERSION             3.499
score BOGUS_MSM_HDRS                 2.785
score CK_HELO_DYNAMIC_SPLIT_IP       1.500
score CK_HELO_GENERIC                0.250
score COMPENSATION                   1.499
score DATE_IN_FUTURE_96_Q            2.260
score DEAR_BENEFICIARY               1.557
score DOS_RCVD_IP_TWICE_B            2.699
score DRUGS_ERECTILE_SHORT_SHORTNER  0.267
score DUP_SUSP_HDR                   2.105
score DX_TEXT_03                     0.677
score EBAY_IMG_NOT_RCVD_EBAY         1.864
score END_FUTURE_EMAILS              2.100
score FAKE_REPLY_A1                  1.887
score FILL_THIS_FORM                 0.000
score FORGED_RELAY_MUA_TO_MX         2.302
score FORM_FRAUD                     0.001
score FORM_FRAUD_5                   0.001
score FOUND_YOU                      3.250
score FREEMAIL_FORGED_FROMDOMAIN     0.183
score FREEM_FRNUM_UNICD_EMPTY        1.928
score FROMSPACE                      2.251
score FROM_2_EMAILS_SHORT            1.478
score FROM_ADDR_WS                   2.999
score FROM_MISSPACED                 0.201
score FROM_MISSP_EH_MATCH            1.999
score FROM_MISSP_FREEMAIL            3.399
score FROM_MISSP_MSFT                1.461
score FROM_MISSP_REPLYTO             2.500
score FROM_MISSP_TO_UNDISC           2.104
score FROM_MISSP_USER                3.104
score FROM_MISSP_XPRIO               2.499
score FROM_NAME_EQ_TO_G_DRIVE        0.001
score FROM_NTLD_REPLY_FREEMAIL       1.555
score FROM_SUSPICIOUS_NTLD           0.499
score FROM_SUSPICIOUS_NTLD_FP        1.999
score FROM_UNBAL1                    3.197
score FROM_WORDY                     0.001
score FROM_WSP_TRAIL                 1.999
score FSL_CTYPE_WIN1251              4.299
score FSL_HELO_FAKE                  3.199
score FSL_NEW_HELO_USER              1.999
score FSL_THIS_IS_ADV                1.799
score FUZZY_CLICK_HERE               2.590
score FUZZY_UNSUBSCRIBE              2.096
score GB_BITCOIN_CP                  2.999
score GB_BITCOIN_NH                  3.000
score GB_FREEMAIL_DISPTO             0.499
score GB_LINKED_IMG_NOT_RCVD_LINK    2.499
score GB_MONERO_CP                   1.168
score HDRS_LCASE                     0.100
score HDRS_LCASE_IMGONLY             0.099
score HDR_ORDER_FTSDMCXX_DIRECT      2.000
score HDR_ORDER_FTSDMCXX_NORDNS      3.461
score HEADER_FROM_DIFFERENT_DOMAINS  0.250
score HELO_MISC_IP                   0.250
score HELO_NO_DOMAIN                 0.000
score HEXHASH_WORD                   2.999
score HK_LOTTO                       0.999
score HK_NAME_MR_MRS                 1.000
score HK_RANDOM_FROM                 1.000
score HK_RANDOM_REPLYTO              0.999
score HK_RCVD_IP_MULTICAST           0.341
score HK_SCAM                        1.999
score HK_WIN                         0.717
score HOSTED_IMG_DIRECT_MX           2.500
score HOSTED_IMG_FREEM               1.133
score HOSTED_IMG_MULTI               1.751
score HTML_ENTITY_ASCII              2.999
score HTML_OFF_PAGE                  2.999
score HTML_SINGLET_MANY              1.876
score HTML_TEXT_INVISIBLE_STYLE      0.001
score IMG_ONLY_FM_DOM_INFO           2.336
score KB_FORGED_MOZ4                 3.999
score KHOP_FAKE_EBAY                 0.001
score KHOP_HELO_FCRDNS               0.400
score LIST_PRTL_SAME_USER            0.001
score LONG_HEX_URI                   2.600
score LONG_IMG_URI                   1.950
score LOTS_OF_MONEY                  0.010
score L_8BIT_MISMATCH                0.010
score MAILER_EQ_ORG                  1.309
score MALFORMED_FREEMAIL             1.653
score MALF_HTML_B64                  2.752
score MALWARE_NORDNS                 3.306
score MALWARE_PASSWORD               3.499
score MAY_BE_FORGED                  1.199
score MILLION_HUNDRED                0.000
score MIMEOLE_DIRECT_TO_MX           1.999
score MIXED_ES                       2.599
score MONERO_EXTORT_01               3.137
score MONEY_ATM_CARD                 2.558
score MONEY_FORM                     0.001
score MONEY_FORM_SHORT               1.935
score MONEY_FRAUD_3                  2.800
score MONEY_FRAUD_5                  2.944
score MONEY_FRAUD_8                  3.099
score MONEY_FROM_41                  1.999
score MONEY_FROM_MISSP               1.999
score MSM_PRIO_REPTO                 2.499
score NEWEGG_IMG_NOT_RCVD_NEGG       1.067
score NORDNS_LOW_CONTRAST            1.874
score NO_FM_NAME_IP_HOSTN            0.001
score NSL_RCVD_FROM_USER             2.062
score NSL_RCVD_HELO_USER             0.141
score NUMBERONLY_BITCOIN_EXP         1.612
score OBFU_BITCOIN                   3.000
score OBFU_TEXT_ATTACH               1.553
score OFFER_ONLY_AMERICA             1.999
score PDS_BTC_HACKER                 1.684
score PDS_BTC_NTLD                   1.999
score PDS_FROM_2_EMAILS              1.699
score PDS_FROM_NAME_TO_DOMAIN        1.000
score PDS_HP_HELO_NORDNS             0.566
score PDS_NAKED_TO_NUMERO            1.999
score PDS_PHPE_URISHORTENER          1.999
score PDS_PHP_EVAL                   1.499
score PDS_TONAME_EQ_TOLOCAL_FREEM_FORGE 1.999
score PDS_TONAME_EQ_TOLOCAL_HDRS_LCASE 1.999
score PDS_TONAME_EQ_TOLOCAL_SHORT    1.999
score PDS_TONAME_EQ_TOLOCAL_VSHORT   0.999
score PDS_TO_EQ_FROM_NAME            0.000
score PDS_X_PHP_WELLKNOWN            0.999
score PDS_X_PHP_WP_EXP               1.499
score PHP_ORIG_SCRIPT                2.499
score PP_MIME_FAKE_ASCII_TEXT        0.999
score RATWARE_NO_RDNS                1.625
score RDNS_NUM_TLD_ATCHNX            1.610
score RDNS_NUM_TLD_XM                2.999
score RISK_FREE                      1.802
score SEO_SUSP_NTLD                  1.200
score SERGIO_SUBJECT_PORN014         3.497
score SERGIO_SUBJECT_VIAGRA01        0.822
score SHOPIFY_IMG_NOT_RCVD_SFY       2.500
score SHORTENER_SHORT_IMG            0.572
score SHORT_BODY_G_DRIVE_DYN         1.499
score SHORT_SHORTNER                 1.999
score SINGLETS_LOW_CONTRAST          0.001
score SPOOFED_FREEMAIL_NO_RDNS       1.499
score STATIC_XPRIO_OLE               1.999
score STOCK_LOW_CONTRAST             2.499
score SUBJ_OBFU_PUNCT_FEW            0.749
score SUBJ_OBFU_PUNCT_MANY           1.749
score SUSPNTLD_EXPIRATION_EXTORT     1.999
score TEQF_USR_IMAGE                 1.391
score THIS_AD                        1.900
score THIS_IS_ADV_SUSP_NTLD          1.499
score TONOM_EQ_TOLOC_SHRT_SHRTNER    1.499
score TO_EQ_FM_DIRECT_MX             1.801
score TO_EQ_FM_DOM_HTML_IMG          0.001
score TO_EQ_FM_DOM_HTML_ONLY         1.702
score TO_EQ_FM_HTML_ONLY             0.000
score TO_IN_SUBJ                     0.100
score TO_NAME_SUBJ_NO_RDNS           1.952
score TO_NO_BRKTS_DYNIP              1.859
score TO_NO_BRKTS_FROM_MSSP          2.499
score TO_NO_BRKTS_HTML_IMG           1.999
score TO_NO_BRKTS_HTML_ONLY          1.999
score TO_NO_BRKTS_MSFT               2.499
score TO_NO_BRKTS_NORDNS_HTML        1.999
score TO_NO_BRKTS_PCNT               2.499
score TVD_SPACE_ENCODED              0.103
score TVD_SPACE_RATIO_MINFP          2.499
score UNICODE_OBFU_ASC               2.499
score UNICODE_OBFU_ZW                0.821
score UPGRADE_MAILBOX                1.399
score URI_GOOGLE_PROXY               2.299
score URI_ONLY_MSGID_MALF            1.653
score URI_PHISH                      3.549
score URI_PHP_REDIR                  3.499
score URI_TRY_3LD                    1.936
score URI_WP_HACKED                  3.499
score URI_WP_HACKED_2                2.499
score US_DOLLARS_3                   1.999
score XPRIO                          2.250
score XPRIO_SHORT_SUBJ               2.499
score XPRIO_URL_SHORTNER             0.226
score ZW_OBFU_BITCOIN                1.663
score ACT_NOW_CAPS                   0.100
score AC_HTML_NONSENSE_TAGS          1.000
score AC_SPAMMY_URI_PATTERNS1        1.000
score AC_SPAMMY_URI_PATTERNS10       1.000
score AC_SPAMMY_URI_PATTERNS11       1.000
score AC_SPAMMY_URI_PATTERNS12       1.000
score AC_SPAMMY_URI_PATTERNS2        1.000
score AC_SPAMMY_URI_PATTERNS3        1.000
score AC_SPAMMY_URI_PATTERNS4        1.000
score AC_SPAMMY_URI_PATTERNS8        1.000
score AC_SPAMMY_URI_PATTERNS9        1.000
score ADVANCE_FEE_2_NEW_FORM         1.000
score ALL_TRUSTED                    -1.000
score ANY_BOUNCE_MESSAGE             0.100
score APOSTROPHE_FROM                0.148
score APP_DEVELOPMENT_FREEM          1.000
score APP_DEVELOPMENT_NORDNS         1.000
score BAD_CREDIT                     0.100
score BAD_ENC_HEADER                 0.001
score BANG_GUAR                      1.000
score BANKING_LAWS                   2.399
score BASE64_LENGTH_78_79            0.100
score BASE64_LENGTH_79_INF           1.379
score BILLION_DOLLARS                0.001
score BITCOIN_BOMB                   1.000
score BITCOIN_DEADLINE               1.000
score BITCOIN_MALWARE                1.000
score BITCOIN_SPAM_03                1.000
score BITCOIN_SPAM_10                1.000
score BITCOIN_SPAM_11                1.000
score BITCOIN_SPAM_12                1.000
score BODY_8BITS                     1.500
score BODY_ENHANCEMENT               0.927
score BODY_ENHANCEMENT2              0.100
score BOMB_FREEM                     1.000
score BOMB_MONEY                     1.000
score BOUNCE_MESSAGE                 0.100
score BTC_ORG                        1.000
score BUG6152_INVALID_DATE_TZ_ABSURD 0.100
score BULK_RE_SUSP_NTLD              1.000
score CANT_SEE_AD                    1.000
score CHALLENGE_RESPONSE             0.100
score CHARSET_FARAWAY                3.200
score CHARSET_FARAWAY_HEADER         3.200
score COMMENT_GIBBERISH              1.000
score CRBOUNCE_MESSAGE               0.100
score CTYPE_001C_B                   0.001
score CURR_PRICE                     0.001
score DATE_IN_FUTURE_03_06           3.399
score DATE_IN_FUTURE_06_12           2.899
score DATE_IN_FUTURE_12_24           2.603
score DATE_IN_FUTURE_24_48           2.598
score DATE_IN_FUTURE_48_96           2.384
score DATE_IN_PAST_03_06             2.399
score DATE_IN_PAST_06_12             1.699
score DATE_IN_PAST_12_24             0.001
score DATE_IN_PAST_24_48             1.109
score DATE_IN_PAST_96_XX             2.600
score DAY_I_EARNED                   1.000
score DC_GIF_UNO_LARGO               0.001
score DC_IMAGE_SPAM_HTML             0.100
score DC_IMAGE_SPAM_TEXT             0.100
score DC_PNG_UNO_LARGO               0.001
score DEAR_FRIEND                    2.683
score DEAR_SOMETHING                 1.999
score DEAR_WINNER                    3.099
score DIET_1                         0.714
score DKIM_INVALID                   0.100
score DOS_OE_TO_MX                   2.602
score DOS_OE_TO_MX_IMAGE             2.886
score DOS_OUTLOOK_TO_MX              2.636
score DOS_RCVD_IP_TWICE_C            2.599
score DOS_STOCK_BAT                  0.001
score DRUGS_ANXIETY                  0.100
score DRUGS_DIET                     2.660
score DRUGS_ERECTILE                 1.778
score DRUGS_ERECTILE_OBFU            1.324
score DRUGS_MANYKINDS                2.001
score DRUGS_MUSCLE                   0.001
score DRUGS_SMEAR1                   3.300
score DRUG_ED_CAPS                   2.799
score DRUG_ED_ONLINE                 0.696
score DRUG_ED_SILD                   0.001
score DYN_RDNS_AND_INLINE_IMAGE      1.345
score DYN_RDNS_SHORT_HELO_HTML       0.001
score DYN_RDNS_SHORT_HELO_IMAGE      1.825
score EMPTY_MESSAGE                  2.195
score EM_ROLEX                       0.595
score ENCRYPTED_MESSAGE              -1.000
score ENGLISH_UCE_SUBJECT            0.953
score EXCUSE_4                       2.399
score EXCUSE_REMOVE                  2.907
score FAKE_REPLY_C                   0.688
score FBI_MONEY                      1.000
score FBI_SPOOF                      1.000
score FILL_THIS_FORM_LOAN            2.092
score FILL_THIS_FORM_LONG            3.800
score FIN_FREE                       0.100
score FORGED_HOTMAIL_RCVD2           0.001
score FORGED_MSGID_EXCITE            2.399
score FORGED_MSGID_YAHOO             0.100
score FORGED_MUA_EUDORA              2.828
score FORGED_MUA_IMS                 2.399
score FORGED_MUA_MOZILLA             2.399
score FORGED_MUA_OIMO                2.600
score FORGED_MUA_OUTLOOK             3.999
score FORGED_MUA_THEBAT_BOUN         3.046
score FORGED_OUTLOOK_HTML            0.001
score FORGED_OUTLOOK_TAGS            0.003
score FORGED_TELESP_RCVD             2.499
score FORGED_YAHOO_RCVD              2.397
score FORM_LOW_CONTRAST              1.000
score FREEMAIL_ENVFROM_END_DIGIT     0.250
score FREEMAIL_FORGED_REPLYTO        1.199
score FREEMAIL_FROM                  0.001
score FREEMAIL_REPLY                 1.000
score FREEMAIL_REPLYTO               1.000
score FREEMAIL_REPLYTO_END_DIGIT     0.250
score FREE_QUOTE_INSTANT             2.700
score FRNAME_IN_MSG_XPRIO_NO_SUB     1.000
score FROM_BLANK_NAME                2.099
score FROM_DOMAIN_NOVOWEL            0.500
score FROM_EXCESS_BASE64             0.001
score FROM_ILLEGAL_CHARS             2.192
score FROM_LOCAL_DIGITS              0.001
score FROM_LOCAL_NOVOWEL             0.500
score FROM_NO_USER                   0.001
score FROM_NTLD_LINKBAIT             1.000
score FROM_NUMERIC_TLD               1.000
score FROM_STARTS_WITH_NUMS          2.801
score FROM_WORDY_SHORT               1.000
score FSL_FAKE_HOTMAIL_RVCD          2.631
score FSL_HELO_BARE_IP_1             2.598
score FSL_HELO_DEVICE                0.100
score FSL_HELO_NON_FQDN_1            2.361
score FSL_INTERIA_ABUSE              3.899
score FUZZY_CPILL                    0.001
score FUZZY_CREDIT                   1.699
score FUZZY_MILLION                  0.100
score FUZZY_PHARMACY                 2.960
score FUZZY_PHENT                    2.799
score FUZZY_PRICES                   1.821
score FUZZY_VPILL                    0.001
score FUZZY_XPILL                    0.100
score GAPPY_SALES_LEADS_FREEM        1.000
score GAPPY_SUBJECT                  0.100
score GB_FORGED_MUA_POSTFIX          1.000
score GB_FREEMAIL_DISPTO_NOTFREEM    0.500
score GB_GOOGLE_OBFU                 0.750
score GB_GOOG_IMG_NOT_RCVD_GOOG      1.000
score GOOGLE_DOCS_PHISH              1.000
score GOOGLE_DOCS_PHISH_MANY         1.000
score GOOGLE_DRIVE_REPLY_BAD_NTLD    1.000
score GOOG_MALWARE_DNLD              1.000
score GTUBE                          1000.000
score GUARANTEED_100_PERCENT         2.699
score HEADER_SPAM                    2.499
score HELO_DYNAMIC_CHELLO_NL         2.412
score HELO_DYNAMIC_DHCP              2.602
score HELO_DYNAMIC_DIALIN            2.629
score HELO_DYNAMIC_HCC               4.299
score HELO_DYNAMIC_HEXIP             2.321
score HELO_DYNAMIC_HOME_NL           2.385
score HELO_DYNAMIC_IPADDR            2.633
score HELO_DYNAMIC_IPADDR2           2.815
score HELO_DYNAMIC_SPLIT_IP          3.031
score HELO_LOCALHOST                 2.639
score HELO_OEM                       2.899
score HELO_STATIC_HOST               -0.001
score HIDE_WIN_STATUS                0.001
score HK_NAME_DRUGS                  4.299
score HK_RANDOM_ENVFROM              2.638
score HOSTED_IMG_DQ_UNSUB            1.000
score HTML_CHARSET_FARAWAY           0.500
score HTML_COMMENT_SAVED_URL         0.198
score HTML_EMBEDS                    0.001
score HTML_ENTITY_ASCII_TINY         1.000
score HTML_EXTRA_CLOSE               0.001
score HTML_FONT_FACE_BAD             0.001
score HTML_FONT_LOW_CONTRAST         0.713
score HTML_FONT_SIZE_HUGE            0.001
score HTML_FONT_SIZE_LARGE           0.001
score HTML_IMAGE_ONLY_04             1.680
score HTML_IMAGE_ONLY_08             0.585
score HTML_IMAGE_ONLY_12             1.381
score HTML_IMAGE_ONLY_16             1.969
score HTML_IMAGE_ONLY_20             2.109
score HTML_IMAGE_ONLY_24             2.799
score HTML_IMAGE_ONLY_28             2.799
score HTML_IMAGE_ONLY_32             2.196
score HTML_IMAGE_RATIO_02            0.001
score HTML_IMAGE_RATIO_04            0.001
score HTML_IMAGE_RATIO_06            0.001
score HTML_IMAGE_RATIO_08            0.001
score HTML_MESSAGE                   0.001
score HTML_MIME_NO_HTML_TAG          0.001
score HTML_OBFUSCATE_05_10           0.601
score HTML_OBFUSCATE_10_20           0.174
score HTML_OBFUSCATE_20_30           2.499
score HTML_OBFUSCATE_90_100          2.000
score HTML_SHORT_CENTER              3.799
score HTML_SHORT_LINK_IMG_1          2.215
score HTML_SHORT_LINK_IMG_2          1.419
score HTML_SHORT_LINK_IMG_3          0.691
score HTML_SHRT_CMNT_OBFU_MANY       1.000
score HTML_TAG_BALANCE_BODY          0.100
score HTML_TAG_BALANCE_HEAD          0.520
score HTML_TEXT_INVISIBLE_FONT       1.000
score HTML_TITLE_SUBJ_DIFF           1.149
score HTTPS_HTTP_MISMATCH            0.100
score HTTP_ESCAPED_HOST              0.100
score HTTP_EXCESSIVE_ESCAPES         0.001
score IMPOTENCE                      1.539
score INVALID_DATE                   1.701
score INVALID_DATE_TZ_ABSURD         0.262
score INVALID_MSGID                  2.602
score INVESTMENT_ADVICE              0.100
score IP_LINK_PLUS                   0.001
score JOIN_MILLIONS                  0.100
score KB_DATE_CONTAINS_TAB           3.800
score KB_FAKED_THE_BAT               2.432
score KB_RATWARE_MSGID               4.099
score KB_RATWARE_OUTLOOK_MID         4.400
score LIST_PARTIAL_SHORT_MSG         1.000
score LIST_PRTL_PUMPDUMP             1.000
score LIVEFILESTORE                  0.100
score LOCALPART_IN_SUBJECT           0.001
score LONGWORDS                      2.199
score LONG_TERM_PRICE                0.001
score LOTTERY_1                      0.001
score LOTTERY_PH_004470              0.100
score LOW_PRICE                      0.100
score LUCRATIVE                      1.000
score L_SPAM_TOOL_13                 0.539
score MALE_ENHANCE                   3.100
score MANY_HDRS_LCASE                0.100
score MARKETING_PARTNERS             0.553
score MICROSOFT_EXECUTABLE           0.100
score MIMEPART_LIMIT_EXCEEDED        0.001
score MIME_BASE64_TEXT               0.001
score MIME_BOUND_DD_DIGITS           3.016
score MIME_BOUND_DIGITS_15           0.100
score MIME_CHARSET_FARAWAY           2.450
score MIME_HEADER_CTYPE_ONLY         0.100
score MIME_HTML_MOSTLY               0.100
score MIME_HTML_ONLY                 0.100
score MIME_NO_TEXT                   1.000
score MIME_PHP_NO_TEXT               2.800
score MIME_QP_LONG_LINE              0.001
score MIME_SUSPECT_NAME              0.100
score MISSING_DATE                   2.739
score MISSING_HEADERS                0.915
score MISSING_MID                    0.552
score MISSING_MIMEOLE                0.392
score MISSING_MIME_HB_SEP            0.001
score MISSING_SUBJECT                0.001
score MONEY_BACK                     2.910
score MORE_SEX                       2.799
score MPART_ALT_DIFF                 2.246
score MPART_ALT_DIFF_COUNT           2.799
score MSGID_FROM_MTA_HEADER          0.401
score MSGID_OUTLOOK_INVALID          3.899
score MSGID_RANDY                    2.196
score MSGID_SHORT                    0.001
score MSGID_SPAM_CAPS                2.366
score MSGID_YAHOO_CAPS               0.797
score MSOE_MID_WRONG_CASE            0.993
score NORMAL_HTTP_TO_IP              0.159
score NO_HEADERS_MESSAGE             0.001
score NO_MEDICAL                     2.199
score NO_PRESCRIPTION                1.915
score NO_RDNS_DOTCOM_HELO            3.100
score NO_RECEIVED                    -0.001
score NO_RELAYS                      -0.001
score NULL_IN_BODY                   0.511
score ONE_TIME                       1.840
score ONLINE_PHARMACY                0.843
score OOOBOUNCE_MESSAGE              0.100
score PART_CID_STOCK                 0.001
score PERCENT_RANDOM                 2.999
score PHOTO_EDITING_DIRECT           1.000
score PHOTO_EDITING_FREEM            1.000
score PHP_NOVER_MUA                  1.000
score PHP_SCRIPT_MUA                 1.000
score PLING_QUERY                    0.100
score PP_TOO_MUCH_UNICODE02          0.500
score PP_TOO_MUCH_UNICODE05          1.000
score PRICES_ARE_AFFORDABLE          0.794
score PUMPDUMP                       1.000
score PUMPDUMP_MULTI                 1.000
score RAND_HEADER_MANY               1.000
score RATWARE_EFROM                  0.100
score RATWARE_EGROUPS                1.898
score RATWARE_MPOP_WEBMAIL           1.153
score RATWARE_MS_HASH                2.036
score RATWARE_NAME_ID                3.099
score RATWARE_OUTLOOK_NONAME         2.964
score RATWARE_ZERO_TZ                2.392
score RCVD_DOUBLE_IP_LOOSE           1.150
score RCVD_DOUBLE_IP_SPAM            2.411
score RCVD_FAKE_HELO_DOTCOM          2.799
score RCVD_HELO_IP_MISMATCH          1.680
score RCVD_ILLEGAL_IP                1.300
score RDNS_DYNAMIC                   2.639
score RDNS_LOCALHOST                 3.700
score RDNS_NONE                      2.399
score REMOVE_BEFORE_LINK             0.100
score REPLICA_WATCH                  3.487
score REPLYTO_WITHOUT_TO_CC          2.399
score REPTO_QUOTE_YAHOO              0.001
score SB_GIF_AND_NO_URIS             2.199
score SHORT_HELO_AND_INLINE_IMAGE    0.100
score SHORT_IMG_SUSP_NTLD            1.000
score SHORT_TERM_PRICE               0.001
score SORTED_RECIPS                  1.801
score SPAMMY_XMAILER                 2.650
score SPOOF_COM2COM                  0.001
score SPOOF_COM2OTH                  0.001
score STOCK_IMG_CTYPE                0.001
score STOCK_IMG_HDR_FROM             0.001
score STOCK_IMG_OUTLOOK              0.001
score STOCK_TIP                      1.000
score STOX_REPLY_TYPE                1.898
score STOX_REPLY_TYPE_WITHOUT_QUOTES 3.099
score SUBJECT_DIET                   1.927
score SUBJECT_DRUG_GAP_C             2.108
score SUBJECT_DRUG_GAP_L             2.799
score SUBJECT_FUZZY_CHEAP            0.641
score SUBJECT_IN_BLACKLIST           100.000
score SUBJECT_IN_WHITELIST           -100.000
score SUBJECT_NEEDS_ENCODING         0.498
score SUBJ_ALL_CAPS                  0.500
score SUBJ_AS_SEEN                   2.711
score SUBJ_BUY                       0.594
score SUBJ_DOLLARS                   0.100
score SUBJ_ILLEGAL_CHARS             0.620
score SUBJ_YOUR_FAMILY               2.910
score SUSPICIOUS_RECIPS              2.499
score SYSADMIN                       1.000
score TBIRD_SUSP_MIME_BDRY           2.400
score THEBAT_UNREG                   2.599
score TO_MALFORMED                   0.100
score TRACKER_ID                     0.100
score TT_MSGID_TRUNC                 0.748
score TVD_FINGER_02                  0.001
score TVD_FW_GRAPHIC_NAME_LONG       0.001
score TVD_FW_GRAPHIC_NAME_MID        0.600
score TVD_INCREASE_SIZE              1.529
score TVD_PH_BODY_ACCOUNTS_PRE       0.001
score TVD_PH_REC                     0.100
score TVD_PH_SEC                     0.100
score TVD_QUAL_MEDS                  2.697
score TVD_RCVD_IP                    0.001
score TVD_RCVD_IP4                   0.001
score TVD_RCVD_SPACE_BRACKET         0.001
score TVD_SPACE_RATIO                0.001
score TVD_SUBJ_ACC_NUM               0.100
score TVD_SUBJ_WIPE_DEBT             2.599
score TVD_VISIT_PHARMA               1.957
score TW_GIBBERISH_MANY              1.000
score UC_GIBBERISH_OBFU              1.000
score UNCLAIMED_MONEY                2.699
score UNCLOSED_BRACKET               2.699
score UNICODE_OBFU_DOM_NO_BODY       1.000
score UNPARSEABLE_RELAY              0.001
score UNRESOLVED_TEMPLATE            3.035
score UNWANTED_LANGUAGE_BODY         2.800
score UPPERCASE_50_75                0.001
score UPPERCASE_75_100               1.480
score URG_BIZ                        1.750
score URI_DATA                       1.000
score URI_HEX                        0.100
score URI_HEX_IP                     1.000
score URI_HOST_IN_BLACKLIST          100.000
score URI_HOST_IN_WHITELIST          -100.000
score URI_IMG_WP_REDIR               1.000
score URI_NOVOWEL                    0.500
score URI_OPTOUT_3LD                 1.000
score URI_TRUNCATED                  0.001
score URI_WP_DIRINDEX                1.000
score USB_DRIVES                     1.000
score USER_IN_ALL_SPAM_TO            -100.000
score USER_IN_BLACKLIST              100.000
score USER_IN_BLACKLIST_TO           10.000
score USER_IN_DEF_WHITELIST          -15.000
score USER_IN_MORE_SPAM_TO           -20.000
score USER_IN_WHITELIST              -100.000
score USER_IN_WHITELIST_TO           -6.000
score VBOUNCE_MESSAGE                0.100
score VPS_NO_NTLD                    1.000
score WALMART_IMG_NOT_RCVD_WAL       1.000
score WEIRD_PORT                     0.001
score WEIRD_QUOTING                  0.001
score X_IP                           0.001
score X_MAILER_CME_6543_MSN          2.886


569.76user 0.38system 9:30.31elapsed 99%CPU (0avgtext+0avgdata 5828maxresident)k
328inputs+6720outputs (2major+1053minor)pagefaults 0swaps
+ date
Sun Oct  6 03:26:59 UTC 2019
+ mv garescorer.scores gen-set0-5-5.0-6000-ga/scores
+ echo [gen run end]
+ cp orig_scores.cf tmprules/50_scores.cf
[gen run end]
+ perl ./rewrite-cf-with-new-scores --scoreset 0 --old-scores tmprules/50_scores.cf --new-scores gen-set0-5-5.0-6000-ga/scores --cffile tmprules
fix meta dep: __OBFU_BITCOIN depends on FUZZY_BITCOIN with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_DIMS depends on GMD_PDF_VERT with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_DIMS depends on GMD_PDF_HORIZ with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_DIMS depends on GMD_PDF_SQUARE with 0 score, fixing at non-0
fix meta dep: FUZZY_BTC_WALLET depends on FUZZY_WALLET with 0 score, fixing at non-0
fix meta dep: FORGED_MUA_EUDORA depends on MAILING_LIST_MULTI with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_PRODUCERS depends on GMD_PRODUCER_GPL with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_PRODUCERS depends on GMD_PRODUCER_POWERPDF with 0 score, fixing at non-0
fix meta dep: __GMD_PDF_PRODUCERS depends on GMD_PRODUCER_EASYPDF with 0 score, fixing at non-0
fix meta dep: __AC_FROM_MANY_DOTS_MINFP depends on FORGED_GMAIL_RCVD with 0 score, fixing at non-0
+ mv tmprules/50_newscores.cf tmprules/50_scores.cf
+ cp tmprules/50_scores.cf gen-set0-5-5.0-6000-ga/50_scores.cf
+ perl ./fp-fn-statistics --ham ham-test.log --spam spam-test.log --scoreset 0 --cffile=tmprules --fnlog gen-set0-5-5.0-6000-ga/false_negatives --fplog gen-set0-5-5.0-6000-ga/false_positives
[../build/parse-rules-for-masses -o tmp/rules_10155.pl -d "tmprules" -s 0]
Sun Oct  6 03:27:59 UTC 2019
[ generating fp-fn-statistics ]
[../build/parse-rules-for-masses -o tmp/rules_16603.pl -d "../rules-base" -s 0]
[../build/parse-rules-for-masses -o tmp/rules_16737.pl -d "../rules-base" -s 0]
Sun Oct  6 03:33:43 UTC 2019
[ extracting new scores ]
Removing scores for base release rules from newly generated scores
# Using score set 0 logs for revision 1867965 from:
# ham-axb-coi-bulk.r1867965.log ham-axb-generic.r1867965.log ham-axb-ham-misc.r1867965.log ham-darxus.r1867965.log ham-ena-week3.r1867965.log ham-ena-week4.r1867965.log ham-giovanni-ham.r1867965.log ham-giovanni-spammy.r1867965.log ham-giovanni-spam.r1867965.log ham-grenier.r1867965.log ham-hege.r1867965.log ham-jarif.r1867965.log ham-jbrooks.r1867965.log ham-llanga.r1867965.log ham-mmiroslaw-mails-ham.r1867965.log ham-mmiroslaw-mails-spam.r1867965.log ham-npiazzi.r1867965.log ham-pds.r1867965.log ham-sihde.r1867965.log ham-spamsponge.r1867965.log ham-thendrikx.r1867965.log spam-axb-coi-bulk.r1867965.log spam-axb-generic.r1867965.log spam-axb-ham-misc.r1867965.log spam-darxus.r1867965.log spam-ena-week3.r1867965.log spam-ena-week4.r1867965.log spam-giovanni-ham.r1867965.log spam-giovanni-spammy.r1867965.log spam-giovanni-spam.r1867965.log spam-grenier.r1867965.log spam-hege.r1867965.log spam-jarif.r1867965.log spam-jbrooks.r1867965.log spam-llanga.r1867965.log spam-mmiroslaw-mails-ha
 m.r1867965.log spam-mmiroslaw-mails-spam.r1867965.log spam-npiazzi.r1867965.log spam-pds.r1867965.log spam-sihde.r1867965.log spam-spamsponge.r1867965.log spam-thendrikx.r1867965.log

score AC_BR_BONANZA                  0.001
score AC_DIV_BONANZA                 0.001
score AC_FROM_MANY_DOTS              2.999
score ADMITS_SPAM                    3.199
score ADVANCE_FEE_2_NEW_MONEY        1.999
score ADVANCE_FEE_3_NEW              2.601
score ADVANCE_FEE_3_NEW_FORM         1.632
score ADVANCE_FEE_3_NEW_FRM_MNY      1.436
score ADVANCE_FEE_3_NEW_MONEY        2.046
score ADVANCE_FEE_4_NEW              2.799
score ADVANCE_FEE_4_NEW_MONEY        2.202
score ADVANCE_FEE_5_NEW              1.396
score ADVANCE_FEE_5_NEW_FRM_MNY      0.001
score ADVANCE_FEE_5_NEW_MONEY        0.006
score AD_PREFS                       0.499
score ALIBABA_IMG_NOT_RCVD_ALI       2.499
score AMAZON_IMG_NOT_RCVD_AMZN       2.249
score ANY_PILL_PRICE                 2.000
score AXB_XMAILER_MIMEOLE_OL_024C2   4.399
score AXB_X_AOL_SEZ_S                2.499
score BITCOIN_EXTORT_01              2.502
score BITCOIN_PAY_ME                 2.999
score BITCOIN_SPAM_01                0.196
score BITCOIN_SPAM_02                2.499
score BITCOIN_SPAM_04                1.499
score BITCOIN_SPAM_06                0.001
score BITCOIN_SPAM_07                3.499
score BITCOIN_SPAM_08                0.247
score BITCOIN_SPAM_09                1.499
score BODY_EMPTY                     1.999
score BODY_URI_ONLY                  0.999
score BOGUS_MIME_VERSION             3.499
score BOGUS_MSM_HDRS                 2.785
score CK_HELO_DYNAMIC_SPLIT_IP       1.500
score CK_HELO_GENERIC                0.250
score COMPENSATION                   1.499
score DATE_IN_FUTURE_96_Q            2.260
score DEAR_BENEFICIARY               1.557
score DOS_RCVD_IP_TWICE_B            2.699
score DRUGS_ERECTILE_SHORT_SHORTNER  0.267
score DUP_SUSP_HDR                   2.105
score DX_TEXT_03                     0.776
score EBAY_IMG_NOT_RCVD_EBAY         1.864
score END_FUTURE_EMAILS              2.100
score FAKE_REPLY_A1                  1.887
score FILL_THIS_FORM                 0.000
score FORGED_RELAY_MUA_TO_MX         2.302
score FORM_FRAUD                     0.001
score FORM_FRAUD_5                   0.001
score FOUND_YOU                      3.250
score FREEMAIL_FORGED_FROMDOMAIN     0.183
score FREEM_FRNUM_UNICD_EMPTY        1.928
score FROMSPACE                      2.251
score FROM_2_EMAILS_SHORT            1.478
score FROM_ADDR_WS                   2.999
score FROM_MISSPACED                 0.201
score FROM_MISSP_EH_MATCH            1.999
score FROM_MISSP_FREEMAIL            3.399
score FROM_MISSP_MSFT                1.461
score FROM_MISSP_REPLYTO             2.500
score FROM_MISSP_TO_UNDISC           2.104
score FROM_MISSP_USER                3.104
score FROM_MISSP_XPRIO               2.499
score FROM_NAME_EQ_TO_G_DRIVE        0.001
score FROM_NTLD_REPLY_FREEMAIL       1.555
score FROM_SUSPICIOUS_NTLD           0.499
score FROM_SUSPICIOUS_NTLD_FP        1.999
score FROM_UNBAL1                    3.197
score FROM_WORDY                     0.001
score FROM_WSP_TRAIL                 1.999
score FSL_CTYPE_WIN1251              4.299
score FSL_HELO_FAKE                  3.199
score FSL_NEW_HELO_USER              1.999
score FSL_THIS_IS_ADV                1.799
score FUZZY_CLICK_HERE               2.590
score FUZZY_UNSUBSCRIBE              2.096
score GB_BITCOIN_CP                  2.999
score GB_BITCOIN_NH                  3.000
score GB_FREEMAIL_DISPTO             0.499
score GB_LINKED_IMG_NOT_RCVD_LINK    2.499
score GB_MONERO_CP                   1.168
score HDRS_LCASE                     0.100
score HDRS_LCASE_IMGONLY             0.099
score HDR_ORDER_FTSDMCXX_DIRECT      2.000
score HDR_ORDER_FTSDMCXX_NORDNS      3.198
score HEADER_FROM_DIFFERENT_DOMAINS  0.250
score HELO_MISC_IP                   0.250
score HELO_NO_DOMAIN                 0.000
score HEXHASH_WORD                   2.999
score HK_LOTTO                       0.999
score HK_NAME_MR_MRS                 1.000
score HK_RANDOM_FROM                 1.000
score HK_RANDOM_REPLYTO              0.999
score HK_RCVD_IP_MULTICAST           0.341
score HK_SCAM                        1.999
score HK_WIN                         0.717
score HOSTED_IMG_DIRECT_MX           2.500
score HOSTED_IMG_FREEM               1.133
score HOSTED_IMG_MULTI               1.751
score HTML_ENTITY_ASCII              2.999
score HTML_OFF_PAGE                  2.999
score HTML_SINGLET_MANY              1.876
score HTML_TEXT_INVISIBLE_STYLE      0.001
score IMG_ONLY_FM_DOM_INFO           2.336
score KB_FORGED_MOZ4                 3.999
score KHOP_FAKE_EBAY                 0.001
score KHOP_HELO_FCRDNS               0.400
score LIST_PRTL_SAME_USER            0.001
score LONG_HEX_URI                   2.600
score LONG_IMG_URI                   1.950
score LOTS_OF_MONEY                  0.010
score L_8BIT_MISMATCH                0.010
score MAILER_EQ_ORG                  1.309
score MALFORMED_FREEMAIL             1.653
score MALF_HTML_B64                  2.752
score MALWARE_NORDNS                 3.306
score MALWARE_PASSWORD               3.499
score MAY_BE_FORGED                  1.199
score MILLION_HUNDRED                0.000
score MIMEOLE_DIRECT_TO_MX           1.999
score MIXED_ES                       2.599
score MONERO_EXTORT_01               3.137
score MONEY_ATM_CARD                 2.558
score MONEY_FORM                     0.001
score MONEY_FORM_SHORT               1.935
score MONEY_FRAUD_3                  2.800
score MONEY_FRAUD_5                  2.944
score MONEY_FRAUD_8                  3.099
score MONEY_FROM_41                  1.999
score MONEY_FROM_MISSP               1.999
score MSM_PRIO_REPTO                 2.499
score NEWEGG_IMG_NOT_RCVD_NEGG       1.067
score NORDNS_LOW_CONTRAST            1.874
score NO_FM_NAME_IP_HOSTN            0.001
score NSL_RCVD_FROM_USER             2.062
score NSL_RCVD_HELO_USER             0.261
score NUMBERONLY_BITCOIN_EXP         1.612
score OBFU_BITCOIN                   3.000
score OBFU_TEXT_ATTACH               1.553
score OFFER_ONLY_AMERICA             1.999
score PDS_BTC_HACKER                 1.684
score PDS_BTC_NTLD                   1.999
score PDS_FROM_2_EMAILS              1.699
score PDS_FROM_NAME_TO_DOMAIN        1.000
score PDS_HP_HELO_NORDNS             0.566
score PDS_NAKED_TO_NUMERO            1.999
score PDS_PHPE_URISHORTENER          1.999
score PDS_PHP_EVAL                   1.499
score PDS_TONAME_EQ_TOLOCAL_FREEM_FORGE 1.999
score PDS_TONAME_EQ_TOLOCAL_HDRS_LCASE 1.999
score PDS_TONAME_EQ_TOLOCAL_SHORT    1.999
score PDS_TONAME_EQ_TOLOCAL_VSHORT   0.999
score PDS_TO_EQ_FROM_NAME            0.000
score PDS_X_PHP_WELLKNOWN            0.999
score PDS_X_PHP_WP_EXP               1.499
score PHP_ORIG_SCRIPT                2.499
score PP_MIME_FAKE_ASCII_TEXT        0.999
score RATWARE_NO_RDNS                1.625
score RDNS_NUM_TLD_ATCHNX            1.610
score RDNS_NUM_TLD_XM                2.999
score RISK_FREE                      1.802
score SEO_SUSP_NTLD                  1.200
score SERGIO_SUBJECT_PORN014         3.497
score SERGIO_SUBJECT_VIAGRA01        0.822
score SHOPIFY_IMG_NOT_RCVD_SFY       2.500
score SHORTENER_SHORT_IMG            0.572
score SHORT_BODY_G_DRIVE_DYN         1.499
score SHORT_SHORTNER                 1.999
score SINGLETS_LOW_CONTRAST          0.001
score SPOOFED_FREEMAIL_NO_RDNS       1.499
score STATIC_XPRIO_OLE               1.999
score STOCK_LOW_CONTRAST             2.499
score SUBJ_OBFU_PUNCT_FEW            0.749
score SUBJ_OBFU_PUNCT_MANY           1.749
score SUSPNTLD_EXPIRATION_EXTORT     1.999
score TEQF_USR_IMAGE                 1.391
score THIS_AD                        1.900
score THIS_IS_ADV_SUSP_NTLD          1.220
score TONOM_EQ_TOLOC_SHRT_SHRTNER    1.499
score TO_EQ_FM_DIRECT_MX             1.801
score TO_EQ_FM_DOM_HTML_IMG          0.001
score TO_EQ_FM_DOM_HTML_ONLY         1.702
score TO_EQ_FM_HTML_ONLY             0.000
score TO_IN_SUBJ                     0.100
score TO_NAME_SUBJ_NO_RDNS           1.952
score TO_NO_BRKTS_DYNIP              1.859
score TO_NO_BRKTS_FROM_MSSP          2.499
score TO_NO_BRKTS_HTML_IMG           1.999
score TO_NO_BRKTS_HTML_ONLY          1.999
score TO_NO_BRKTS_MSFT               2.499
score TO_NO_BRKTS_NORDNS_HTML        1.999
score TO_NO_BRKTS_PCNT               2.499
score TVD_SPACE_ENCODED              0.103
score TVD_SPACE_RATIO_MINFP          2.499
score UNICODE_OBFU_ASC               2.499
score UNICODE_OBFU_ZW                0.821
score UPGRADE_MAILBOX                1.399
score URI_GOOGLE_PROXY               2.299
score URI_ONLY_MSGID_MALF            1.653
score URI_PHISH                      3.549
score URI_PHP_REDIR                  3.499
score URI_TRY_3LD                    1.936
score URI_WP_HACKED                  3.499
score URI_WP_HACKED_2                2.499
score US_DOLLARS_3                   1.999
score XPRIO                          2.250
score XPRIO_SHORT_SUBJ               2.499
score XPRIO_URL_SHORTNER             0.226
score ZW_OBFU_BITCOIN                1.663
score AC_HTML_NONSENSE_TAGS          1.000
score AC_SPAMMY_URI_PATTERNS1        1.000
score AC_SPAMMY_URI_PATTERNS10       1.000
score AC_SPAMMY_URI_PATTERNS11       1.000
score AC_SPAMMY_URI_PATTERNS12       1.000
score AC_SPAMMY_URI_PATTERNS2        1.000
score AC_SPAMMY_URI_PATTERNS3        1.000
score AC_SPAMMY_URI_PATTERNS4        1.000
score AC_SPAMMY_URI_PATTERNS8        1.000
score AC_SPAMMY_URI_PATTERNS9        1.000
score ADVANCE_FEE_2_NEW_FORM         1.000
score APP_DEVELOPMENT_FREEM          1.000
score APP_DEVELOPMENT_NORDNS         1.000
score BITCOIN_BOMB                   1.000
score BITCOIN_DEADLINE               1.000
score BITCOIN_MALWARE                1.000
score BITCOIN_SPAM_03                1.000
score BITCOIN_SPAM_10                1.000
score BITCOIN_SPAM_11                1.000
score BITCOIN_SPAM_12                1.000
score BOMB_FREEM                     1.000
score BOMB_MONEY                     1.000
score BTC_ORG                        1.000
score BULK_RE_SUSP_NTLD              1.000
score CANT_SEE_AD                    1.000
score COMMENT_GIBBERISH              1.000
score DAY_I_EARNED                   1.000
score ENCRYPTED_MESSAGE              -1.000
score FBI_MONEY                      1.000
score FBI_SPOOF                      1.000
score FORM_LOW_CONTRAST              1.000
score FRNAME_IN_MSG_XPRIO_NO_SUB     1.000
score FROM_NTLD_LINKBAIT             1.000
score FROM_NUMERIC_TLD               1.000
score FROM_WORDY_SHORT               1.000
score GAPPY_SALES_LEADS_FREEM        1.000
score GB_FORGED_MUA_POSTFIX          1.000
score GB_FREEMAIL_DISPTO_NOTFREEM    0.500
score GB_GOOGLE_OBFU                 0.750
score GB_GOOG_IMG_NOT_RCVD_GOOG      1.000
score GOOGLE_DOCS_PHISH              1.000
score GOOGLE_DOCS_PHISH_MANY         1.000
score GOOGLE_DRIVE_REPLY_BAD_NTLD    1.000
score GOOG_MALWARE_DNLD              1.000
score HOSTED_IMG_DQ_UNSUB            1.000
score HTML_ENTITY_ASCII_TINY         1.000
score HTML_SHRT_CMNT_OBFU_MANY       1.000
score HTML_TEXT_INVISIBLE_FONT       1.000
score LIST_PARTIAL_SHORT_MSG         1.000
score LIST_PRTL_PUMPDUMP             1.000
score LUCRATIVE                      1.000
score MANY_HDRS_LCASE                0.100
score MIME_NO_TEXT                   1.000
score PHOTO_EDITING_DIRECT           1.000
score PHOTO_EDITING_FREEM            1.000
score PHP_NOVER_MUA                  1.000
score PHP_SCRIPT_MUA                 1.000
score PP_TOO_MUCH_UNICODE02          0.500
score PP_TOO_MUCH_UNICODE05          1.000
score PUMPDUMP                       1.000
score PUMPDUMP_MULTI                 1.000
score RAND_HEADER_MANY               1.000
score SHORT_IMG_SUSP_NTLD            1.000
score STOCK_TIP                      1.000
score SYSADMIN                       1.000
score TW_GIBBERISH_MANY              1.000
score UC_GIBBERISH_OBFU              1.000
score UNICODE_OBFU_DOM_NO_BODY       1.000
score URI_DATA                       1.000
score URI_HEX_IP                     1.000
score URI_IMG_WP_REDIR               1.000
score URI_OPTOUT_3LD                 1.000
score URI_WP_DIRINDEX                1.000
score USB_DRIVES                     1.000
score VPS_NO_NTLD                    1.000
score WALMART_IMG_NOT_RCVD_WAL       1.000
# in active.list but have no hits in recent corpus
score BITCOIN_SPAM_05                0.000
score BITCOIN_SPF_ONLYALL            0.000
score DKIMWL_BL                      0.000
score DKIMWL_BLOCKED                 0.000
score DKIMWL_WL_HIGH                 0.000
score DKIMWL_WL_MED                  0.000
score DKIMWL_WL_MEDHI                0.000
score FROM_BANK_NOAUTH               0.000
score FROM_FMBLA_NDBLOCKED           0.000
score FROM_FMBLA_NEWDOM              0.000
score FROM_FMBLA_NEWDOM14            0.000
score FROM_FMBLA_NEWDOM28            0.000
score FROM_GOV_DKIM_AU               0.000
score FROM_GOV_REPLYTO_FREEMAIL      0.000
score FROM_GOV_SPOOF                 0.000
score FROM_MISSP_SPF_FAIL            0.000
score FROM_NEWDOM_BTC                0.000
score FROM_NUMBERO_NEWDOMAIN         0.000
score FROM_PAYPAL_SPOOF              0.000
score FSL_BULK_SIG                   0.000
score PDS_HELO_SPF_FAIL              0.000
score RCVD_IN_MSPIKE_BL              0.000
score RCVD_IN_MSPIKE_H2              0.000
score RCVD_IN_MSPIKE_H3              0.000
score RCVD_IN_MSPIKE_H4              0.000
score RCVD_IN_MSPIKE_H5              0.000
score RCVD_IN_MSPIKE_L2              0.000
score RCVD_IN_MSPIKE_L3              0.000
score RCVD_IN_MSPIKE_L4              0.000
score RCVD_IN_MSPIKE_L5              0.000
score RCVD_IN_MSPIKE_WL              0.000
score RCVD_IN_MSPIKE_ZBI             0.000
score SPOOFED_FREEMAIL               0.000
score SPOOFED_FREEM_REPTO            0.000
score SPOOFED_FREEM_REPTO_CHN        0.000
score SPOOFED_FREEM_REPTO_RUS        0.000
score SURBL_BLOCKED                  0.000
score TO_EQ_FM_DOM_SPF_FAIL          0.000
score TO_EQ_FM_SPF_FAIL              0.000
Sun Oct  6 03:33:43 UTC 2019
[ completed ]
/usr/local/spamassassin/automc/tmp/generate-new-scores
Sun Oct  6 03:33:43 UTC 2019
[ rsyncing logs ]
[ rsyncing logs locally ]
sending incremental file list

sent 4,887 bytes  received 12 bytes  9,798.00 bytes/sec
total size is 30,991,718,032  speedup is 6,326,131.46
Sun Oct  6 03:33:43 UTC 2019
[ selecting log files to use for scoreset 1 ]
Linked ham-net-pds.runknown.log to corpus/usable-corpus-set1/ham-net-pds.runknown.log
Linked ham-net-sihde.runknown.log to corpus/usable-corpus-set1/ham-net-sihde.runknown.log
Linked spam-net-grenier.runknown.log to corpus/usable-corpus-set1/spam-net-grenier.runknown.log
Linked ham-net-mmiroslaw-mails-ham.runknown.log to corpus/usable-corpus-set1/ham-net-mmiroslaw-mails-ham.runknown.log
Linked ham-net-ena-week3.runknown.log to corpus/usable-corpus-set1/ham-net-ena-week3.runknown.log
Linked spam-net-thendrikx.runknown.log to corpus/usable-corpus-set1/spam-net-thendrikx.runknown.log
Linked ham-net-axb-coi-bulk.runknown.log to corpus/usable-corpus-set1/ham-net-axb-coi-bulk.runknown.log
Linked spam-net-hege.runknown.log to corpus/usable-corpus-set1/spam-net-hege.runknown.log
Linked ham-net-ena-week0.runknown.log to corpus/usable-corpus-set1/ham-net-ena-week0.runknown.log
Linked spam-net-ena-week4.runknown.log to corpus/usable-corpus-set1/spam-net-ena-week4.runknown.log
Linked spam-net-ena-week0.runknown.log to corpus/usable-corpus-set1/spam-net-ena-week0.runknown.log
Linked ham-net-spamsponge.runknown.log to corpus/usable-corpus-set1/ham-net-spamsponge.runknown.log
Linked ham-net-thendrikx.runknown.log to corpus/usable-corpus-set1/ham-net-thendrikx.runknown.log
Linked spam-net-llanga.r1867656.log to corpus/usable-corpus-set1/spam-net-llanga.r1867656.log
Linked spam-net-jbrooks.runknown.log to corpus/usable-corpus-set1/spam-net-jbrooks.runknown.log
Linked spam-net-ena-week3.runknown.log to corpus/usable-corpus-set1/spam-net-ena-week3.runknown.log
Linked ham-net-llanga.r1867656.log to corpus/usable-corpus-set1/ham-net-llanga.r1867656.log
Linked ham-net-grenier.runknown.log to corpus/usable-corpus-set1/ham-net-grenier.runknown.log
Linked spam-net-axb-generic.runknown.log to corpus/usable-corpus-set1/spam-net-axb-generic.runknown.log
Linked spam-net-spamsponge.runknown.log to corpus/usable-corpus-set1/spam-net-spamsponge.runknown.log
Linked ham-net-ena-week4.runknown.log to corpus/usable-corpus-set1/ham-net-ena-week4.runknown.log
Linked ham-net-axb-ham-misc.runknown.log to corpus/usable-corpus-set1/ham-net-axb-ham-misc.runknown.log
Linked spam-net-npiazzi.runknown.log to corpus/usable-corpus-set1/spam-net-npiazzi.runknown.log
Linked spam-net-sihde.runknown.log to corpus/usable-corpus-set1/spam-net-sihde.runknown.log
Linked spam-net-axb-ham-misc.runknown.log to corpus/usable-corpus-set1/spam-net-axb-ham-misc.runknown.log
Linked ham-net-npiazzi.runknown.log to corpus/usable-corpus-set1/ham-net-npiazzi.runknown.log
Linked spam-net-pds.runknown.log to corpus/usable-corpus-set1/spam-net-pds.runknown.log
Linked spam-net-mmiroslaw-mails-spam.runknown.log to corpus/usable-corpus-set1/spam-net-mmiroslaw-mails-spam.runknown.log
Linked ham-net-darxus.runknown.log to corpus/usable-corpus-set1/ham-net-darxus.runknown.log
Linked spam-net-axb-coi-bulk.runknown.log to corpus/usable-corpus-set1/spam-net-axb-coi-bulk.runknown.log
Linked ham-net-mmiroslaw-mails-spam.runknown.log to corpus/usable-corpus-set1/ham-net-mmiroslaw-mails-spam.runknown.log
Linked spam-net-mmiroslaw-mails-ham.runknown.log to corpus/usable-corpus-set1/spam-net-mmiroslaw-mails-ham.runknown.log
Linked ham-net-axb-generic.runknown.log to corpus/usable-corpus-set1/ham-net-axb-generic.runknown.log
Linked spam-net-darxus.runknown.log to corpus/usable-corpus-set1/spam-net-darxus.runknown.log
Linked ham-net-hege.runknown.log to corpus/usable-corpus-set1/ham-net-hege.runknown.log
Linked spam-net-jarif.runknown.log to corpus/usable-corpus-set1/spam-net-jarif.runknown.log
Linked ham-net-jarif.runknown.log to corpus/usable-corpus-set1/ham-net-jarif.runknown.log
Linked ham-net-jbrooks.runknown.log to corpus/usable-corpus-set1/ham-net-jbrooks.runknown.log

Majority SVN revision found: unknown

Checking corpus/usable-corpus-set1/ham-net-pds.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-sihde.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-grenier.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-mmiroslaw-mails-ham.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-ena-week3.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-thendrikx.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-axb-coi-bulk.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-hege.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-ena-week0.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-ena-week4.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-ena-week0.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-spamsponge.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-thendrikx.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-llanga.r1867656.log for SVN unknown...
corpus/usable-corpus-set1/spam-net-llanga.r1867656.log does not meet the requirements
Checking corpus/usable-corpus-set1/spam-net-jbrooks.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-ena-week3.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-llanga.r1867656.log for SVN unknown...
corpus/usable-corpus-set1/ham-net-llanga.r1867656.log does not meet the requirements
Checking corpus/usable-corpus-set1/ham-net-grenier.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-axb-generic.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-spamsponge.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-ena-week4.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-axb-ham-misc.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-npiazzi.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-sihde.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-axb-ham-misc.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-npiazzi.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-pds.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-mmiroslaw-mails-spam.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-darxus.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-axb-coi-bulk.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-mmiroslaw-mails-spam.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-mmiroslaw-mails-ham.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-axb-generic.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-darxus.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-hege.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/spam-net-jarif.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-jarif.runknown.log for SVN unknown...
# SVN revision: unknown
Checking corpus/usable-corpus-set1/ham-net-jbrooks.runknown.log for SVN unknown...
# SVN revision: unknown
 HAM CONTRIBUTORS FOUND: 18 (required 8)
SPAM CONTRIBUTORS FOUND: 18 (required 8)
Sun Oct  6 03:33:44 UTC 2019
[ checking out code from svn repository ]
+ svn co -r unknown http://svn.apache.org/repos/asf/spamassassin/trunk trunk-new-rules-set1
svn: E205000: Syntax error in revision argument 'unknown'
+ exit 1
+ RV=1
+ '[' 1 -ne 0 ']'
+ echo 'Exit Status 1 is not zero for do-nightly-rescore-example'
Exit Status 1 is not zero for do-nightly-rescore-example
+ echo 'From: noreply@spamassassin.apache.org (automc Cron)'
+ echo 'Subject: [auto] do-nightly-rescore-example return code 1'
+ echo ''
+ echo 'Exit Status 1 is not zero for do-nightly-rescore-example.'
+ /usr/sbin/sendmail -oi ruleqa@spamassassin.apache.org