Mini toolsDefinition
A family of unsupervised learning methods that group similar data points into clusters.
Detailed Explanation
Clustering algorithms identify natural groupings in data based on similarity measures. They can be hierarchical (creating nested clusters) or partitional (creating flat clusters), and may use various distance metrics and criteria for forming clusters. The choice of algorithm depends on data characteristics and clustering objectives.
Use Cases
1. Customer segmentation 2. Image segmentation 3. Document clustering 4. Anomaly detection
