For K-12 Students · k-Nearest Neighbors
k-Nearest Neighbors for a pathfinding AI
Built for k-12 students learning it in middle or high school. Watch the idea come alive with plain-language steps and everyday examples — perfect for projects and homework. Simulate a pathfinding AI live below — adjust the inputs and watch it respond, right in your browser.
k-Nearest NeighborsLive
classify by your neighbors
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Presets
k-NN classifies a point by majority vote of its k nearest labeled neighbors. Small k gives jagged, overfit boundaries that chase noise; large k smooths them out but can blur real structure. It is the simplest possible classifier — no training at all. Educational tool.
Data Inspector
Neighbors5
Boundarybalanced
Governing equation
Reading this result: k = 5 sits in the sweet spot: enough neighbors to shrug off noise, few enough to keep the true boundary shape.
Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.
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Frequently asked questions
- Is this good for k-12 students?
- Yes — this version of "k-Nearest Neighbors for a pathfinding AI" is framed for k-12 students learning it in middle or high school. Watch the idea come alive with plain-language steps and everyday examples — perfect for projects and homework.
- Do I need to install anything?
- No. It runs in any modern browser, free, with no account required.