diff --git a/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md b/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md
index 8d87b27..e9b72a9 100644
--- a/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md	
+++ b/Running Start/CSB320 - Machine Learning Concepts/Class 5-21 (Ensemble Models).md	
@@ -36,4 +36,7 @@ bootstrap_samples = [
 	- 10-25 decision trees are typically sufficient
 		- too many results in diminishing returns
 	- bagging gives high accuracy and better generalization but can be hard to interpret and have large computational costs
+- random forests
+	- uses decision trees trained on feature subsets
+	- predictions are aggregated using averaging (regression) or majority vote (classification)
 	- 
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