Frbs: Fuzzy Rule-based Systems for Classification and Regression in R

Document Outline

• Introduction
• Fuzzy rule-based systems
  • Overview of FRBSs
    • The Mamdani model
    • The TSK model
  • Variants of FRBSs
  • Constructing FRBSs
• Package architecture and implementation details
  • FRBSs based on space partition approaches
  • FRBSs based on neural networks
  • FRBSs based on genetic algorithms
  • FRBSs based on clustering approaches
  • FRBSs based on the gradient descent approach
• Using the frbs package
  • Preprocessing
  • Model generation
  • Prediction with new data
• Experimental study: Comparison with other packages
  • Regression tasks
    • Datasets
    • Methods considered for comparison and their parameters
    • Experimental results
  • Classification tasks
    • Datasets
    • Methods considered for comparison and their parameters
    • Experimental results
• Other FRBS packages available on CRAN
• Conclusions