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Running Start/CSB320 - Machine Learning Concepts/Class 4-16 (Classification Models).md

@@ -115,4 +115,7 @@ 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
+- Each feature has an equal importance when predicting the output class
+### Linear Discriminant Analysis
+
+Linear Discriminant Analysis (LDA) is a supervised learning method that is used to reduce the dimensionality of a dataset. It attempts to maximize the distance between groups and minimize the variation within classes. Since it is supervised it knows the category labels and uses them to maximize the distance between classes.