diff --git a/docs/en/stack/ml/rules.asciidoc b/docs/en/stack/ml/rules.asciidoc
index dad9654ee..017a0863b 100644
--- a/docs/en/stack/ml/rules.asciidoc
+++ b/docs/en/stack/ml/rules.asciidoc
@@ -1,9 +1,6 @@
 [role="xpack"]
 [[ml-rules]]
-=== Machine learning custom rules
-++++
-<titleabbrev>Custom Rules</titleabbrev>
-++++
+=== Custom rules
 
 By default, as described in <<ml-analyzing>>, anomaly detection is unsupervised 
 and the {ml} models have no awareness of the domain of your data. As a result, 
@@ -11,7 +8,7 @@ and the {ml} models have no awareness of the domain of your data. As a result,
 uninteresting when you know the larger context. Machine learning custom rules
 enable you to customize anomaly detection. 
 
-_Rules_ instruct anomaly detectors to change their behavior based on 
+_Custom rules_ instruct anomaly detectors to change their behavior based on 
 domain-specific knowledge that you provide. When you create a rule, you can  
 specify conditions, scope, and actions. When the conditions of a rule are 
 satisfied, its actions are triggered.