Clustering is a term used to describe a machine learning technique used to group similar data points together based on their features. Unlike classification, which assigns predefined labels, clustering discovers natural groupings in the data without prior labels.
- Glossary > Letter: C
What does "Clustering" mean?

Use Cases
Customer Segmentation:
Grouping customers based on purchasing behavior for targeted marketing.
Image Segmentation:
Dividing an image into regions with similar characteristics.
Anomaly Detection:
Identifying unusual patterns in data, such as fraud detection.

Importance
Pattern Discovery:
Helps uncover hidden patterns and relationships in data.
Data Simplification:
Reduces the complexity of data by summarizing it into clusters.
Insight Generation:
Provides insights that can inform business decisions and strategies.

Analogies
Clustering is like organizing a library without a catalog. You sort books into groups based on their topics and similarities, even though you don’t have predefined labels for each group.
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