Decision Tree learns a set of if/then rules from your data. It’s the most interpretable model in the toolbox — you can trace exactly why a prediction was made.Documentation Index
Fetch the complete documentation index at: https://docs.clickml.app/llms.txt
Use this file to discover all available pages before exploring further.
Configuration
| Parameter | Description | Default |
|---|---|---|
| Max Depth | Maximum tree depth. Shallower trees generalize better. Leave empty for unlimited. | None |
| Min Samples Split | Minimum samples to split a node. | 2 |
| Min Samples Leaf | Minimum samples in a leaf node. | 1 |
| Criterion | Split quality measure: gini or entropy | gini |
| Random State | Seed for reproducibility. | 42 |
Input / Output
| Type | |
|---|---|
| Input | X Train + Y Train |
| Output | Trained Model |