Hierarchical Clustering vs K-Means: Key Differences
Clustering is a critical technique in unsupervised machine learning, widely used for grouping similar data points into clusters without any predefined labels. It is particularly important for uncovering hidden patterns in large datasets, enabling better decision-making in areas like customer segmentation, anomaly detection, and image processing. By identifying inherent groupings, clustering helps businesses and researchers … Read more