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ClusteringAdvancedK-meansPCAStandardScaler

K-means Clustering + PCA

Clusters Wisconsin breast cancer data and visualizes in PCA space.

Key highlights

  • Standardizes features
  • Clusters into 2 groups
  • Reports accuracy after label alignment

Metrics

Confusion matrixAccuracy

Dataset

Wisconsin Breast Cancer

View full codeDownload dataset

Outputs

K-means clustering plot
Clusters visualized in PCA space

Code snapshot

Key lines that anchor the experiment workflow.

kmeans = KMeans(n_clusters=2, random_state=42, n_init=10)
y_kmeans = kmeans.predict(X_scaled)
print(confusion_matrix(y, y_kmeans))

Next steps

Want to explore further? Try the full gallery or open the raw script to tweak parameters.

Back to galleryOpen code on GitHub