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For Hobbyists & Makers · k-Nearest Neighbors

k-Nearest Neighbors for a convolutional net

Built for hobbyists & makers exploring it for fun. Play with real physics and math, no license and no setup — just open and tinker. Simulate a convolutional net live below — adjust the inputs and watch it respond, right in your browser.

k-Nearest NeighborsLive

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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.

▶ Run in Python

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 hobbyists & makers?
Yes — this version of "k-Nearest Neighbors for a convolutional net" is framed for hobbyists & makers exploring it for fun. Play with real physics and math, no license and no setup — just open and tinker.
Do I need to install anything?
No. It runs in any modern browser, free, with no account required.