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
  • Prerequisites
  • Prepare Your Dataset
  • Train a Model and Extract Rules
  • Analyze and Refine the Rules
  • Make Predictions
    • Single-sample prediction
    • Batch prediction (vectorized)
  • Compare Metrics
  • Exporting the Classifier
    • Export to standalone Python
    • Export to binary
    • Export to C header
  • Saving and Loading
  • Editing
• Examples
  • COVID-19
    • Prerequisites
    • Prepare Your Dataset
    • Training the Tree and Extracting Its Rules
    • Pruning
    • Editing
    • Using the model
      • Single-sample prediction
      • Batch prediction
      • Comparing Metrics
      • Exporting
  • DDOS
    • Prerequisites
    • Prepare Your Dataset
    • Training the Forest and Extracting Its Rules
    • Pruning
    • Editing
    • Using the model
      • Single-sample prediction
      • Batch prediction
      • Comparing Metrics
      • Exporting