Decision tree builder.
Build interpretable decision rules from CSV data. Explore splits, impurity, and the path an example takes through a tree.
Your experiment starts here
Ready to explore?
Runs in your browser.
CSV processing happens in your browser. This page does not upload your dataset.
Quick start
Get hands-on.
Use the sample data, paste a CSV, or upload your own. Select a target, adjust the tree settings, and build. Inspect a row or export the model.
What to look for
- Greedy CART-style splitting for numeric and categorical features.
- Gini impurity and entropy for classification; MSE for regression.
- Depth, sample-count, and gain limits that control tree complexity.