Research Explorer

Project

Granular approximations for interpretable hierarchical rule-based systems
Code
01D11322
Duration
01 November 2022 → 31 October 2026
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Knowledge representation and reasoning
Keywords
fuzzy set theory granular computing explainable artificial intelligence
 
Project description
 

I will create a collection of models for multi-class classification, ordinal classification and regression, based on a hierarchical rule-based system with local areas of higher granularity where the granules will be learned from the data using similarity learning and granular approximation. I will simultaneously develop a mathematical formulation of explainability in the context of granular computing.