diff --git a/Running Start/CSB320 - Machine Learning Concepts/Class 4-16 (Classification Models).md b/Running Start/CSB320 - Machine Learning Concepts/Class 4-16 (Classification Models).md
index ce2f20d..9ba596f 100644
--- a/Running Start/CSB320 - Machine Learning Concepts/Class 4-16 (Classification Models).md	
+++ b/Running Start/CSB320 - Machine Learning Concepts/Class 4-16 (Classification Models).md	
@@ -115,4 +115,6 @@ The posterior probability ( $P(A|B)$ ) is the probability that $A$ happens given
 
 The algorithm is referred to as "naive" because it makes a few assumptions:
 - There is no correlation between the features in the dataset, they are all independent
-- Each feature has an equal importance when predicting the output class
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+- Each feature has an equal importance when predicting the output class
+
+testing
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