Decision trees map a series of choices and their outcomes in a branching structure. Each internal node represents a question or condition, each branch represents a possible answer, and leaf nodes represent final outcomes. They are widely used in business strategy, machine learning classification, customer support troubleshooting, and clinical diagnosis. viz42 generates clear, hierarchical decision trees from natural language.
viz42 can generate decision trees with many levels of depth. For readability, we recommend keeping trees under 6-7 levels; deeper trees can be split into sub-trees.
Yes. Include probabilities or weights in your prompt (e.g., '70% likely to...') and viz42 will label the branches accordingly.
You can export the Mermaid code or JSON structure, which can be programmatically parsed into if-else logic or rule engine configurations.