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Running Start/CSB320 - Machine Learning Concepts/Class 5-28 (Clustering).md

@@ -32,4 +32,7 @@
 			- elbow method
 				- graph inertia against k and find point where elbow of data is (curve levels off)
 			- Silhouette method
-				- Use silhouette coeffic
+				- Use silhouette coefficient to determine separation of clusters $$S(j) = \frac{{\overline{d_{out}(j)} - \overline{d_{in}(j)}}}{max(\overline{d_{out}(j)}, \overline{d_{in}(j)})}$$
+				- $\overline{d_{out}(j)}$ is the average distance of the instance $i$ to the centroid of all other clusters
+				- $\overline{d_{in}(j)}$ is the average distance of the instance $i$ to all other instances in its cluster
+				-