2017-03-02 11:23:23 +01:00
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classifier "bayes" {
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tokenizer {
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name = "osb";
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}
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backend = "redis";
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servers = "redis:6379";
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min_tokens = 11;
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min_learns = 20;
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2017-12-09 09:08:18 +01:00
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autolearn = [-20, 50];
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2017-03-02 11:23:23 +01:00
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per_user = <<EOD
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return function(task)
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local rcpt = task:get_recipients(1)
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if rcpt then
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one_rcpt = rcpt[1]
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if one_rcpt['domain'] then
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return one_rcpt['domain']
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end
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end
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return nil
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end
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EOD
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statfile {
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symbol = "BAYES_HAM";
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spam = false;
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}
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statfile {
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symbol = "BAYES_SPAM";
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spam = true;
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}
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learn_condition =<<EOD
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return function(task, is_spam, is_unlearn)
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local prob = task:get_mempool():get_variable('bayes_prob', 'double')
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if prob then
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local in_class = false
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local cl
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if is_spam then
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cl = 'spam'
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in_class = prob >= 0.95
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else
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cl = 'ham'
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in_class = prob <= 0.05
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end
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if in_class then
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return false,string.format('already in class %s; probability %.2f%%',
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cl, math.abs((prob - 0.5) * 200.0))
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end
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end
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return true
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end
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EOD
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}
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