K-Means Clustering
AI/ML Fundamentals
Partitions data into K clusters
What is K-Means Clustering?
Iteratively assigns points to nearest centroid and updates centroids until convergence.
Real-World Examples
- •Customer segmentation
- •Image compression
- •Anomaly detection
When to Use This
Simple, fast clustering when K is known
Related Terms
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