DBSCAN (Density-Based Spatial Clustering of Applications with Noise):
DBSCAN identifies clusters based on data density.
It's particularly effective in distinguishing noise from meaningful patterns.
Mean Shift:
Mean Shift identifies clusters by locating the peaks in data density.
It adapts to varying cluster shapes and sizes.
Applications of Cluster Rush:
Customer Segmentation:
Businesses utilize clustering to categorize customers based on purchasing behavior, demographics, or preferences.
Image Segmentation:
In computer vision, clustering aids in segmenting images, identifying distinct regions or objects.
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