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- # 3. Hierarchical Clustering - Dendrogram
- plt.figure(figsize=(10, 6))
- dendrogram(linkage(X_scaled, method='ward'))
- plt.title("Dendrogram (Hierarchical Clustering)")
- plt.xlabel("Data Points")
- plt.ylabel("Euclidean Distance")
- plt.show()
- # 4. Agglomerative Clustering
- hc = AgglomerativeClustering(n_clusters=3, affinity='euclidean', linkage='ward')
- hc_labels = hc.fit_predict(X_scaled)
- plt.figure(figsize=(6, 5))
- plt.scatter(X_scaled[:, 0], X_scaled[:, 1], c=hc_labels, cmap='Accent', s=50)
- plt.title("Agglomerative Hierarchical Clustering")
- plt.show()
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