GEnI-FR: Granularity to Ensure Interpretability of the Fuzzy Rules

While Fuzzy Rule-Based System (FRBS) is a valuable tool for mapping knowledge from datasets, its balance between accuracy and interpretability remains a challenge. In this paper, we propose a method that utilizes FRBS to enhance interpretability while maintaining accuracy by managing uncertainty and adjusting fuzzy sets based on data characteristics. The results demonstrate the effectiveness of our approach in achieving the balance between interpretability and accuracy by applying the principle of justifiable granularity.