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.
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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