What kind of tree does this build?

It builds a full binary tree where every internal node is a yes or no question and every leaf is an outcome. A depth of three, for example, asks up to three questions before reaching a result.

How many outcomes can the tree end in?

The number of leaves doubles with each level, so a depth-N tree has 2 to the power N leaves. Each leaf is filled with a random outcome from the domain's outcome list, and outcomes can repeat across leaves.

Is this a trained machine learning model?

No. It is a randomly generated rule tree for demos and illustration, not a model fitted to data. The questions and outcomes come from curated domain lists, not from learning on a dataset.

Can I undo a wrong answer while walking?

Yes. A Back button removes your last answer and returns you one level up the tree, and Start over resets to the root so you can explore a different path.

Why does the same depth give the same tree?

The generator is seeded, so the same domain, depth, and seed reproduce the same tree. Clicking Regenerate advances the seed to produce a different arrangement of questions and outcomes.

Decision Tree Generator

A decision tree generator that builds a binary yes/no tree for a chosen domain and lets you walk it interactively to a final outcome. It is handy for chatbot logic mockups, routing demos, and explaining how rule-based decision flows work.

How it works

Pick a domain — support routing, loan approval, medical triage, or spam filtering — and a depth. The generator recursively builds a full binary tree: every internal node is a question drawn from the domain’s question bank, and every leaf at the chosen depth is filled with an outcome from the domain’s outcome list. Because each level branches into two, a depth-N tree has 2^N leaves.

You can walk the tree by answering Yes or No, descending one level per answer until you hit a leaf and see the outcome. A Back button steps up one level and Start over returns to the root. The tree is seeded for reproducibility, so the same settings reproduce the same tree, and Regenerate advances the seed.

Tips and example

Keep the depth modest — two or three — for a readable tree; depth five already produces 32 leaves. The full tree prints as an indented flowchart, for example:

Is the customer a paying subscriber?
Yes: Did the issue start in the last 24 hours?
    Yes: → Escalate to Tier 2
    No:  → Send self-help article
No:  → Close as resolved

Walk it to demo a routing flow, then copy the full tree as plain text for a spec or slide. Remember the questions and outcomes are illustrative samples, not a model trained on real data.