this paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. the classification performance andinterpretability are of major importance in these systems. in this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). ourapproach uses a punish...

This paper considers the automatic design of fuzzy rule-basedclassification systems based on labeled data. The classification performance andinterpretability are of major importance in these systems. In this paper, weutilize the distribution of training patterns in decision subspace of each fuzzyrule to improve its initially assigned certainty grade (i.e. rule weight). Ourapproach uses a punish...

Background: Ankle injuries are one of the most common complaints of patients presenting to emergency departments (ED). The Ottawa ankle rules (OAR) was introduced to help physicians to decide who may require x-ray for blunt injuries. The present study aimed at validating the four steps weight-bearing rule of OAR as a sole criterion.    Methods: This prospective observational study wa...

The Divide and Distribute Fixed Weights algorithm (ddfw) is a dynamic local search SAT-solving that transfers weight from satisfied to falsified clauses in minima. ddfw remarkably effective on several hard combinatorial instances. Yet, despite its success, it has received little study since debut 2005. In this paper, we propose three modifications the base algorithm: linear transfer method move...

In fuzzy rule-based classification systems, rule weight has often been used to improve the classification accuracy. In past research, a number of heuristic methods for rule weight specification have been proposed. In this paper, a method of fuzzy rule weight specification using Receiver Operating Characteristic (ROC) analysis is proposed. In order to specify the weight of a fuzzy rule, using 2-...