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-rw-r--r--lualib/lua_bayes_learn.lua16
1 files changed, 9 insertions, 7 deletions
diff --git a/lualib/lua_bayes_learn.lua b/lualib/lua_bayes_learn.lua
index 7782d8196..ea97db6f8 100644
--- a/lualib/lua_bayes_learn.lua
+++ b/lualib/lua_bayes_learn.lua
@@ -40,7 +40,7 @@ exports.can_learn = function(task, is_spam, is_unlearn)
end
if in_class then
- return false,string.format(
+ return false, string.format(
'already in class %s; probability %.2f%%',
cl, math.abs((prob - 0.5) * 200.0))
end
@@ -56,7 +56,7 @@ exports.autolearn = function(task, conf)
local mime_rcpts = 'undef'
local mr = task:get_recipients('mime')
if mr then
- for _,r in ipairs(mr) do
+ for _, r in ipairs(mr) do
if mime_rcpts == 'undef' then
mime_rcpts = r.addr
else
@@ -76,8 +76,8 @@ exports.autolearn = function(task, conf)
end
-- We have autolearn config so let's figure out what is requested
- local verdict,score = lua_verdict.get_specific_verdict("bayes", task)
- local learn_spam,learn_ham = false, false
+ local verdict, score = lua_verdict.get_specific_verdict("bayes", task)
+ local learn_spam, learn_ham = false, false
if verdict == 'passthrough' then
-- No need to autolearn
@@ -117,12 +117,14 @@ exports.autolearn = function(task, conf)
local ham_learns = task:get_mempool():get_variable('ham_learns', 'int64') or 0
local min_balance = 0.9
- if conf.min_balance then min_balance = conf.min_balance end
+ if conf.min_balance then
+ min_balance = conf.min_balance
+ end
if spam_learns > 0 or ham_learns > 0 then
local max_ratio = 1.0 / min_balance
local spam_learns_ratio = spam_learns / (ham_learns + 1)
- if spam_learns_ratio > max_ratio and learn_spam then
+ if spam_learns_ratio > max_ratio and learn_spam then
lua_util.debugm(N, task,
'skip learning spam, balance is not satisfied: %s < %s; %s spam learns; %s ham learns',
spam_learns_ratio, min_balance, spam_learns, ham_learns)
@@ -130,7 +132,7 @@ exports.autolearn = function(task, conf)
end
local ham_learns_ratio = ham_learns / (spam_learns + 1)
- if ham_learns_ratio > max_ratio and learn_ham then
+ if ham_learns_ratio > max_ratio and learn_ham then
lua_util.debugm(N, task,
'skip learning ham, balance is not satisfied: %s < %s; %s spam learns; %s ham learns',
ham_learns_ratio, min_balance, spam_learns, ham_learns)