How to Find Optimal Epsilon Value for DBSCAN Clustering? §

Metadata §

• Author: Avi Chawla
• Full Title: How to Find Optimal Epsilon Value for DBSCAN Clustering?
• URL: https://www.blog.dailydoseofds.com/p/how-to-find-optimal-epsilon-value

Highlights §

• DBSCAN has three hyperparameters:
  1. Epsilon: two points are considered neighbors if they are closer than Epsilon.
  2. min_samples: Min neighbors for a point to be classified as a core point.
  3. The distance metric. We can use the Elbow Curve to find an optimal value of Epsilon:

  Set k as the min_samples hyperparameter. For every data point, plot the distance to its kth nearest neighbor (in increasing order). The optimal value of Epsilon is found near the elbow point. (View Highlight)