Simulated Annealing
Machine Learning
A metric that measures how similar an object is to its own cluster compared to other clusters.
Detailed Explanation
The Silhouette Score evaluates clustering quality by comparing intra-cluster similarity to inter-cluster similarity. Values range from -1 to 1, where a high score indicates well-defined, cohesive clusters, and a low score suggests overlaps or incorrect clustering. It helps determine the optimal number of clusters and assess the consistency of the clustering results.
Use Cases
- •Use case: Optimize the number of clusters in customer segmentation to improve marketing strategy accuracy.
Related Terms
Other terms in the Machine Learning category