classifier "bayes" {
	tokenizer {
		name = "osb";
	}
	cache {}
	new_schema = true;
	store_tokens = false;
	signatures = false;
	min_tokens = 11;
	backend = "redis";
	min_learns = 200;
	statfile {
		symbol = "BAYES_HAM";
		spam = false;
	}
	statfile {
		symbol = "BAYES_SPAM";
		spam = true;
	}
	learn_condition = 'return require("lua_bayes_learn").can_learn';

	autolearn {
		spam_threshold = 6.0; # When to learn spam (score >= threshold)
		ham_threshold = -0.5; # When to learn ham (score <= threshold)
		check_balance = true; # Check spam and ham balance
		min_balance = 0.9; # Keep diff for spam/ham learns for at least this value
	}
}