How do I evaluate the results of my clustering algorithm?

How do I evaluate the results of my clustering algorithm?

You can evaluate clustering results using metrics like silhouette score, Davies-Bouldin index, or visual inspection.

What is the silhouette score and how is it calculated?

The silhouette score measures how similar an object is to its own cluster compared to other clusters. It's calculated using the formula: (b - a) / max(a, b), where 'a' is the average distance to points in the same cluster, and 'b' is the average distance to points in the nearest cluster.

Can you explain the Davies-Bouldin index?

The Davies-Bouldin index is a ratio of within-cluster scatter to between-cluster separation. A lower value indicates better clustering.

Are there any visual methods to evaluate clustering?

Yes, you can use methods like the elbow method, silhouette plots, or t-SNE visualizations to assess clustering quality.