Neuro-Fuzzy Toolbox

Contents:

  • Introduction
  • Installation
  • Usage
    • Models
      • ANFIS Model Basics
        • 1. Import
        • 2. Instantiation
        • 3. Selected Methods
        • 4. Forward and predict methods
      • ANFIS variants
        • 1. Classical ANFIS
        • 2. Homogeneous ANFIS
        • 3. Rule-reduced ANFIS
      • Output Types on ANFIS Models
        • 1. Multiple Outputs
        • 2. Output Types
    • Training
      • Initial Considerations
        • Model inputs and outputs
        • PyTorch DataLoaders
        • Validation and test sets
        • Early Stopping
        • Available training algorithms
      • Hybrid Learning Algorithm
        • Instantiation
      • Basic Optimizer Training Algorithm
        • Instantiation
      • Double Optimizer Training Algorithm
        • Instantiation
      • SONFIS
        • Instantiation
      • Custom Training
        • 1. Accessing parameters for optimizers
        • 2. Structural modification
        • 3. Accessing intermediate layer outputs
        • 4. Practical example: greedy rule-growing
    • Rule Inspection and Analysis
      • 1. Instantiation
      • 2. Inspecting intermediate layer outputs
      • 3. Identifying the most active rules
        • Return type
        • DataFrame columns
        • Sorting criteria
        • Examples
      • 4. Full prediction explanation
      • 5. Inspecting the global fuzzy structure
      • 6. Sample-specific antecedents
  • Examples
    • Example 1: Multiclass Classification on Iris Dataset
      • Imports and reproducibility
      • Data
      • DataLoaders
      • Model
      • Learning algorithm
      • Evaluation
      • Rule structure analysis
    • Example 2: Multiclass Classification on Glass Identification Dataset
      • Imports and reproducibility
      • Data
      • DataLoaders
      • Model
      • Initial training
      • Initial evaluation
      • Custom strategy: greedy rule-growing
        • Helper function
        • Hyperparameters
        • Rule-growing loop
      • Final evaluation
    • Example 3: Binary Classification on Heart Disease Dataset using SONFIS
      • Imports and reproducibility
      • Data
      • DataLoaders
      • Model
      • Learning algorithm
      • SONFIS
      • Evaluation
    • Example 4: Regression on a 3D Surface using SONFIS
      • Imports and reproducibility
      • Visualization helper
      • Data
      • DataLoaders
      • Model
      • Learning algorithm
      • SONFIS
      • Evaluation
  • API Reference
    • Functions
      • Membership Functions
        • Gaussian_MF
        • GeneralizedBell_MF
        • HighSlopeBell_MF
      • Consequent Functions
        • Linear_CF
    • Layers
      • Fuzzification Layers
        • FuzzificationLayer
        • h_FuzzificationLayer
        • rule_reduced_FuzzificationLayer
      • Firing Levels Layers
        • FiringLevelsLayer
        • NormalizationLayer
        • h_FiringLevelsLayer
        • rule_reduced_FiringLevelsLayer
      • Consequent Layer
        • ConsequentLayer
        • alt_ConsequentLayer
      • Output Layer
        • OutputLayer
    • Models
      • ANFIS Models
        • ANFIS
        • h_ANFIS
        • rule_reduced_ANFIS
        • base_ANFIS
    • Training
      • Early Stopping
        • EarlyStopping
      • Update Strategies
        • OLS Estimation for Consequents
        • Optimizer Training Epoch
      • Training Algorithms
        • Hybrid Learning Algorithm
        • Basic Optimizer Based Training Algorithm
        • Double Optimizer Based Training Algorithm
        • Base Model Trainer
      • SONFIS
        • SONFIS
    • Rule Analyzer
      • Rule Analyzer
        • RulesAnalyzer
Neuro-Fuzzy Toolbox
  • Neuro-Fuzzy Toolbox documentation
  • View page source

Neuro-Fuzzy Toolbox documentation

Welcome to the Neuro-Fuzzy Toolbox documentation.

Contents:

  • Introduction
  • Installation
  • Usage
    • Models
    • Training
    • Rule Inspection and Analysis
  • Examples
    • Example 1: Multiclass Classification on Iris Dataset
    • Example 2: Multiclass Classification on Glass Identification Dataset
    • Example 3: Binary Classification on Heart Disease Dataset using SONFIS
    • Example 4: Regression on a 3D Surface using SONFIS
  • API Reference
    • Functions
    • Layers
    • Models
    • Training
    • Rule Analyzer
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