Overview
Cluster analysis is a powerful tool in data science that helps in grouping similar data points to uncover patterns and insights. By using various algorithms like K-means and hierarchical clustering, analysts can segment data effectively, which is crucial in fields such as marketing, image recognitio...
Key Terms
Example: In customer segmentation, a cluster may represent a group of customers with similar buying habits.
Example: Using K-means to segment customers into different groups based on purchasing behavior.
Example: A dendrogram can illustrate how clusters are formed in hierarchical clustering.
Example: A high silhouette score indicates well-defined clusters.
Example: Starting with individual points and merging them into clusters.
Example: Lower inertia values indicate better clustering.