X-FCS: a fuzzy classifier system using accuracy based fitness - first results
نویسندگان
چکیده
A fuzzy classifier system called X-FCS is proposed which employs accuracy-based fitness. Each classifier (rule) maintains an estimate of the payoff obtained when it fires and the accuracy of this prediction is used as the basis for selection under action of the genetic algorithm. The motivation behind this approach is that such a classifier system will be capable of generating compact, high-performance rule sets which are simultaneously general, accurate and coadapted.
منابع مشابه
A Fall Detection System based on the Type II Fuzzy Logic and Multi-Objective PSO Algorithm
The Elderly health is an important and noticeable issue; since these people are priceless resources of experience in the society. Elderly adults are more likely to be severely injured or to die following falls. Hence, fast detection of such incidents may even lead to saving the life of the injured person. Several techniques have been proposed lately for the fall detection of people, mostly cate...
متن کاملClassifier Fitness Based on Accuracy Stewart
In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier's fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier's fitness is given by a measure of the prediction's accuracy. T h e system executes the genetic algorithm in ...
متن کاملA Framework for Evolving Fuzzy Classifier Systems Using Genetic Programming
A fuzzy classifier system framework is proposed which employs a tree-based representation for fuzzy rule (classifier) antecedents and genetic programming for fuzzy rule discovery. Such a rule representation is employed because of the expressive power and generality it endows to individual rules. The framework proposes accuracy-based fitness for individual fuzzy classifiers and employs evolution...
متن کاملThyroid disorder diagnosis based on Mamdani fuzzy inference system classifier
Introduction: Classification and prediction are two most important applications of statistical methods in the field of medicine. According to this note that the classical classification are provided due to the clinical symptom and do not involve the use of specialized information and knowledge. Therefore, using a classifier that can combine all this information, is necessary. The aim of this s...
متن کاملA Fuzzy Classifier System Using Hyper-Cone Membership Functions and Its Application to Inverted Pendulum Control
This paper proposes a fuzzy classifier system (FCS) using fuzzy rules given by hyper-cone membership functions. The hyper-cone membership function is expressed by a kind of radial basis function, and its fuzzy rules can be flexibly located in input and output spaces. Therefore, The FCS can generate excellent rules which have the best location and shape of membership functions. We apply the FCS ...
متن کامل