User Guide

The Ex-Fuzzy User Guide provides comprehensive documentation for all aspects of building, training, and analyzing fuzzy rule-based classifiers.

Core Concepts

• Core Concepts
  • What is Fuzzy Logic?
  • Fuzzy Sets
  • Linguistic Variables
  • Fuzzy Rules
  • Fuzzy Inference Systems
  • Rule Learning and Optimization
  • Interpretability and Explainability
  • Common Patterns and Best Practices
  • Next Steps
• Choosing a Workflow
  • Classifier Choices
  • Fuzzy Set Types
  • Backend Choices
  • Minimal Example
  • Reproducibility
• Rule Mining Guide
  • Overview
  • Getting Started
  • Mining Parameters
  • Advanced Mining Techniques
  • Rule Quality Assessment
  • Visualization and Analysis
  • Integration with Classifiers
  • Large Dataset Strategies
  • Best Practices
  • Next Steps
• Conformal Learning
  • What You Get
  • Key Concepts
  • Core API
  • Typical Workflow
  • Example: Train and Calibrate
  • Wrapping an Existing Classifier
  • Practical Notes
• Troubleshooting
  • Import Errors
  • EvoX or JAX Installation
  • Slow Training
  • Unexpected Accuracy Differences
  • Documentation Build Issues

Overview

This user guide is organized into several sections:

Core Concepts

Learn about the fundamental building blocks of Ex-Fuzzy: fuzzy sets, classifiers, and optimization algorithms.

Choosing a Workflow

Match common modeling goals to the appropriate classifier, rule-mining path, fuzzy-set type, and backend.

Practical Guides

Get practical advice on rule mining, conformal prediction, troubleshooting common issues, and extending Ex-Fuzzy for your needs.

Getting Help

If you can’t find what you’re looking for in this guide:

• Check the Examples for practical examples

• Consult the API Reference for detailed API documentation

• Ask questions on our GitHub Discussions

• Report bugs on our Issue Tracker