Do I need to install anything?

No. It runs in any modern browser, free, with no account required.

For Educators · Naive Bayes

Naive Bayes for a ranking model

Built for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs. Simulate a ranking model live below — adjust the inputs and watch it respond, right in your browser.

Naive Bayes ClassifierLive

classification by probability

Controls

Presets

Class 1 mean

Class 2 mean

Spread σ

Prior P(class 1)

Naive Bayes models each class as a probability distribution and assigns a new point to whichever class makes it most likely, weighted by the prior. Where the weighted curves cross is the decision boundary. It is fast, simple, and famously strong on text. Educational tool.

▶ Run in Python

Data Inspector

Decision boundary0.28

Class overlaplow (easy)

Governing equation

P (C ∣ x) \propto P (C) N (x; μ_{C}, 1), P (C_{1}) = 0.5, \hat{C} = ar g C max

Reading this result: Well-separated classes with a balanced prior put the boundary right between the means, exactly where the two weighted curves cross.

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 educators?: Yes — this version of "Naive Bayes for a ranking model" is framed for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs.
Do I need to install anything?: No. It runs in any modern browser, free, with no account required.