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Step 8

🎯 Cluster Visualization

See how K-Means has divided 200 customers into 5 distinct segments.

Customer Segments — Annual Income vs Spending Score
Customer Count per Cluster
Cluster Feature Comparison (Radar)
📍 Cluster Centroids (Original Scale)
Centroids shown here are converted back to the original feature scale using inverse_transform(), making them directly interpretable as average income and spending for each cluster.
ClusterAvg Annual Income (k$)Avg Spending ScoreIncome LevelSpending Level
Cluster 0 55.3 49.5 Mid Mid
Cluster 1 86.5 82.1 High High
Cluster 2 25.7 79.4 Low High
Cluster 3 88.2 17.1 High Low
Cluster 4 26.3 20.9 Low Low
81
Cluster 0
40.5% of total
39
Cluster 1
19.5% of total
22
Cluster 2
11.0% of total
35
Cluster 3
17.5% of total
23
Cluster 4
11.5% of total
Next: Cluster Interpretation