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🌳 Hierarchical Clustering and Dendrograms

Watch agglomerative hierarchical clustering merge customer data points into a 3D dendrogram tree step by step, compare linkage methods, and slide a cut-height plane to carve out flat clusters.

Algorithms & AI3DAdvanced60 FPS

Watch agglomerative hierarchical clustering merge customer data points into a 3D dendrogram tree step by step, compare linkage methods, and slide a cut-height plane to carve out flat clusters.

🔬 What It Demonstrates

Each branch fork in the rising tree is a merge of the two nearest clusters; its height is the distance at which they merged. The linkage method changes which pair counts as "nearest," reshaping the whole tree.

🎮 How to Use

Pick a linkage method and point count, then slide the cut-height plane up and down — every branch it crosses splits into a separate, distinctly colored flat cluster on the ground below.

💡 Did You Know?

Because the full tree is built once, changing the cut height is instant — no re-clustering needed, unlike k-means where changing k means starting over.

⚙ Under the hood

Watch agglomerative hierarchical clustering merge customer data points into a 3D dendrogram tree step by step, compare linkage methods, and slide a cut-height plane to carve out flat clusters.

clusteringhierarchicaldendrogramdata-analysismachine-learningvisualizationThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install