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author | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2019-07-24 13:23:23 +0100 |
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committer | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2019-07-24 13:23:23 +0100 |
commit | ebf85df69089ca407d280df4cfaeb865e1e455f1 (patch) | |
tree | 0a0e045744f42a73948c787244a8880b233c2f8a /lualib | |
parent | 8b98f9dd6ab621460ac4d9fbdcb409fa1e65453b (diff) | |
download | rspamd-ebf85df69089ca407d280df4cfaeb865e1e455f1.tar.gz rspamd-ebf85df69089ca407d280df4cfaeb865e1e455f1.zip |
[Rework] Use a dedicated library for autolearn
Diffstat (limited to 'lualib')
-rw-r--r-- | lualib/lua_bayes_learn.lua | 49 |
1 files changed, 49 insertions, 0 deletions
diff --git a/lualib/lua_bayes_learn.lua b/lualib/lua_bayes_learn.lua new file mode 100644 index 000000000..70cbb96c0 --- /dev/null +++ b/lualib/lua_bayes_learn.lua @@ -0,0 +1,49 @@ +--[[ +Copyright (c) 2019, Vsevolod Stakhov <vsevolod@highsecure.ru> + +Licensed 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. +]]-- + +-- This file contains functions to simplify bayes classifier auto-learning + +local exports = {} + +exports.autolearn = function(task, is_spam, is_unlearn) + local learn_type = task:get_request_header('Learn-Type') + + if not (learn_type and tostring(learn_type) == 'bulk') then + local prob = task:get_mempool():get_variable('bayes_prob', 'double') + + if prob then + local in_class = false + local cl + if is_spam then + cl = 'spam' + in_class = prob >= 0.95 + else + cl = 'ham' + in_class = prob <= 0.05 + end + + if in_class then + return false,string.format( + 'already in class %s; probability %.2f%%', + cl, math.abs((prob - 0.5) * 200.0)) + end + end + end + + return true +end + +return exports
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