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API Reference

This section documents the public surface of ANFIS Toolbox. Use it alongside the user guides and examples when you need precise signatures, parameters, and return types.

Estimators

  • ANFISRegressor – Scikit-learn style interface for Takagi–Sugeno–Kang regression.
  • ANFISClassifier – Classification counterpart with probability predictions and evaluation helpers.

Membership Functions

Thirteen membership function families covering Gaussian, bell, sigmoidal, and piecewise-linear shapes are documented in membership-functions.md. Each entry includes parameters, derivative support, and usage examples.

Training

  • Optimizers – Gradient-based, hybrid, and swarm trainers are described in optim.md with configuration notes and supported hyper-parameters.
  • Losses – Regression and classification objectives (and their gradients) are listed in losses.md.

Metrics

Evaluation helpers for regression, classification, and clustering are grouped in metrics.md. Each function documents expected inputs and output formats so you can integrate metrics into experiments or monitoring.

Core Internals

  • Models – Low-level ANFIS graph classes and their rule representations live in models.md.
  • Layers – Individual computational layers and their tensor operations are explained in layers.md.

These pages are useful when you need to inspect or extend the internal pipeline that powers the high-level estimators.

Utilities

  • Configuration – Utilities for persisting and replaying setups appear in config.md.
  • Logging – Structured training logs and logging configuration are covered in logging.md.

Advanced Topics

  • Builders – Advanced model construction hooks are described in builders.md. Most users can rely on estimator defaults.
  • Clustering – The fuzzy C-means implementation used for membership initialization is detailed in clustering.md.

Where to Start

  • New to ANFIS Toolbox? Begin with the models overview.
  • Looking for ready-to-run notebooks? Browse the Examples section in the navigation.
  • Exploring code while reading docs? The “View source” actions in each page jump straight to the implementation.