Tutorials
The following pages serve as an introduction to the functionalities of this package. They will guide you on how to set up and organize your pipeline to include the RuleClassifier and utilize it to extract, prune, and export decision rules from Decision Tree, Random Forest, and Gradient Boosting Decision Trees models.
- Usage
- Modeling for Arduino / ESP32
- Why pyruleanalyzer for Arduino?
- Resource Constraints by Board
- Decision Tree Strategies
- Random Forest Strategies
- Gradient Boosting Decision Trees (GBDT) Strategies
- Feature Selection Strategies
- Memory Validation
- Depth vs. Accuracy Trade-off
- Choosing a Board
- Example Workflows
- Optimization Checklist
- Troubleshooting
- API Reference
- See Also
- Examples