-- at least (10 * (1 - 0.25)) = 8 trains
local max_len = math.max(lua_util.unpack(lua_util.values(lens)))
- local len_bias_check_pred = function(l)
+ local len_bias_check_pred = function(_, l)
return l >= rule.train.max_trains * (1.0 - rule.train.classes_bias)
end
if max_len >= rule.train.max_trains and fun.all(len_bias_check_pred, lens) then
rspamd_logger.debugm(N, rspamd_config,
'checked %s vectors in ANN %s: %s vectors; %s required, need to check other class vectors',
what, ann_key, ntrains, rule.train.max_trains)
+ cont_cb()
end
end
end