/usr/share/perl5/Mail/SpamAssassin/Bayes/CombineNaiveBayes.pm is in spamassassin 3.4.1-8build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | # Naive-Bayesian-style probability combining and related constants.
#
# <@LICENSE>
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to you under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# </@LICENSE>
use strict; # make Test::Perl::Critic happy
# this package is a no-op; the real impl code is in another pkg.
package Mail::SpamAssassin::Bayes::CombineNaiveBayes; 1;
# Force into another package, so our symbols will appear in that namespace with
# no indirection, for speed. Other combiners must do the same, since Bayes.pm
# uses this namespace directly. This means only one combiner can be loaded at
# any time.
package Mail::SpamAssassin::Bayes::Combine;
use strict;
use warnings;
use bytes;
use re 'taint';
###########################################################################
# Value for 'x' in Gary Robinson's f(w) equation.
# "Let x = the number used when n [hits] is 0."
our $FW_X_CONSTANT = 0.600;
# Value for 's' in the f(w) equation. "We can see s as the "strength" (hence
# the use of "s") of an original assumed expectation ... relative to how
# strongly we want to consider our actual collected data." Low 's' means
# trust collected data more strongly.
our $FW_S_CONSTANT = 0.160;
# (s . x) for the f(w) equation.
our $FW_S_DOT_X = ($FW_X_CONSTANT * $FW_S_CONSTANT);
# Should we ignore tokens with probs very close to the middle ground (.5)?
# tokens need to be outside the [ .5-MPS, .5+MPS ] range to be used.
our $MIN_PROB_STRENGTH = 0.430;
###########################################################################
# Combine probabilities using Gary Robinson's naive-Bayesian-style
# combiner
sub combine {
my ($ns, $nn, $sortedref) = @_;
my $wc = scalar @$sortedref;
return unless $wc;
my $P = 1;
my $Q = 1;
foreach my $pw (@$sortedref) {
$P *= (1-$pw);
$Q *= $pw;
}
$P = 1 - ($P ** (1 / $wc));
$Q = 1 - ($Q ** (1 / $wc));
return (1 + ($P - $Q) / ($P + $Q)) / 2.0;
}
1;
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