Do I need to install anything?

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

For Researchers · Decision Tree

Decision Tree for a fraud detector

Built for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model. Simulate a fraud detector live below — adjust the inputs and watch it respond, right in your browser.

Decision Tree SplitsLive

carving space into boxes

Controls

Presets

Depth

Split on X

Split on Y

A decision tree repeatedly splits the feature space along one axis at a time, carving it into rectangular regions each assigned a class. Deeper trees fit more complex boundaries but risk overfitting. Tune the splits to separate the two colors. Educational tool.

▶ Run in Python

Data Inspector

Accuracy100%

Regions4

Governing equation

Gini = 1 - i \sum p_{i}^{2} \Rightarrow accuracy = 100%

Reading this result: Two axis-aligned splits near the center carve the plane into four boxes that match the classes — depth 2 is exactly enough to solve XOR.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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Also for:Students Educators Engineers Hobbyists & Makers K-12 Students First Responders General version →

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Frequently asked questions

Is this good for researchers?: Yes — this version of "Decision Tree for a fraud detector" is framed for researchers prototyping or validating an idea. Prototype fast, reproduce exactly, and share a citable, interactive version of your model.
Do I need to install anything?: No. It runs in any modern browser, free, with no account required.