Rule and Density Behavior in Rule-Dynamical Systems

A Margin-based Model with a Fast Local Searchnewline for Rule Weighting and Reduction in Fuzzynewline Rule-based Classification Systems

Fuzzy Rule-Based Classification Systems (FRBCS) are highly investigated by researchers due to their noise-stability and  interpretability. Unfortunately, generating a rule-base which is sufficiently both accurate and interpretable, is a hard process. Rule weighting is one of the approaches to improve the accuracy of a pre-generated rule-base without modifying the original rules. Most of the pro...

NEW CRITERIA FOR RULE SELECTION IN FUZZY LEARNING CLASSIFIER SYSTEMS

Designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing Fuzzy Learning Classifier (FLC) systems. Conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. In thispaper new entities namely precision and recall from the field of Information Retrieval (IR)systems is adapted as alternative...

Persia and the Golden Rule

My paper has two parts. First, I talk about the golden rule. After introducing the rule and its global importance, I explain why many scholars dismiss it as a vague proverb that leads to absurdities when we try to formulate it clearly. I defend the golden rule against such objections. Second, I talk about the golden rule in Persia and Islam; I consider Persian sources (Muslim and non-Muslim) an...

Adaptability, interpretability and rule weights in fuzzy rule-based systems

This paper discusses interpretability in two main categories of fuzzy systems fuzzy rule-based classifiers and interpolative fuzzy systems. Our goal is to show that the aspect of high level interpretability is more relevant to fuzzy classifiers, whereas fuzzy systems employed in modeling and control benefit more from low-level interpretability. We also discuss the interpretabilityaccuracy trade...

Rule Abstraction: Understanding Emergent Behavior in Swarm Systems