Section 1 — What you will learn
✓ By the end you will understand
- K: how many colonies (groups) the AI tries to form.
- Assignment step: each point joins its nearest star (centroid).
- Update step: each star moves to the average of its claimed points.
- Convergence: stars stop moving → the solution stabilizes.
- Distance metric: Euclidean vs Manhattan changes “nearest”.
- Elbow method: how to pick a good K using inertia (total mess energy).
How to play: Press Start to watch the cinematic 4 phases.
Click in the arena to add new particles (AI will re-balance).
Click in the arena to add new particles (AI will re-balance).
Section 2 — Controls
Story helps kids remember what “grouping without labels” means.
Tip: try K=2 vs K=6 on the same dataset.
Noise is visual: wind lines, point jitter, and outlier meteors.
Section 3 — Live stats
Inertia (Total Mess Energy)
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Centroid Movement
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Convergence
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Outliers (meteors)
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Iterations
0
Best K (Elbow guess)
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Live Chart
Inertia drops as AI improves
Elbow Method
Elbow = point after which adding more colonies barely reduces mess.
Section 4 — Live math (simple)
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🧠 Kid Coach
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Tip: Watch lasers (assignment) and star movement (update).