DBSCAN by Hand: eps, minPts and Core, Border & Noise Points
This lesson is part of the course
In this lesson
You run DBSCAN's labelling step on Tallow's 12 stores with COUNTIF and COUNTIFS on the distance matrix and find the store that belongs to no cluster.
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Lessons in this course
- Distance Matrices: Euclidean, Manhattan & Why Scaling Comes First Locked
- Agglomerative Clustering: Single vs Complete Linkage, Step by Step Locked
- Reading a Dendrogram: Merge Heights, the Largest Gap & Cluster Labels Locked
- Silhouette Score per Store: a, b, s and the Average Locked
- Choosing k: Elbow Rule vs Silhouette Locked
- k-Medoids (PAM): Total Cost and One Swap Step Locked
- DBSCAN by Hand: eps, minPts and Core, Border & Noise Points Locked
- Cluster Profiling and a Scatter Chart Coloured by Cluster Locked