نتایج جستجو برای: tree fuzzy rule based classifier

تعداد نتایج: 3203079  

Journal: :Int. J. Approx. Reasoning 2004
Kenichi Kaieda Shigeo Abe

In a fuzzy classifier with ellipsoidal regions, a fuzzy rule, which is based on the Mahalanobis distance, is defined for each class. Then the fuzzy rules are tuned so that the recognition rate of the training data is maximized. In most cases, one fuzzy rule per one class is enough to obtain high generalization ability. But in some cases, we need to partition the class data to define more than o...

Journal: :Fuzzy Sets and Systems 2004
Frank Hoffmann

This paper presents a novel boosting algorithm for genetic learning of fuzzy classification rules. The method is based on the iterative rule learning approach to fuzzy rule base system design. The fuzzy rule base is generated in an incremental fashion, in that the evolutionary algorithm optimizes one fuzzy classifier rule at a time. The boosting mechanism reduces the weight of those training in...

2008
Luís A. Lucas Tania M. Centeno Myriam R. Delgado

This paper proposes a fuzzy classifier based on type-2 fuzzy sets to be applied in land cover classification. The classifier is built on the basis of the available data and considers the merging of information drawn from different experts. The data regard a thematic mapper representing the land cover of a real plain cultivated area. The experts are represented by different bands which classify ...

2001
Brian Carse Anthony G. Pipe

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-per...

2001
Frank Hoffmann

This paper presents a new boosting algorithm for genetic learning of fuzzy classification rules. The method is based on the iterative rule learning approach to fuzzy rule base system design. The fuzzy rule base is built in an incremental fashion, in that the evolutionary algorithm extracts one fuzzy classifier rule at a time. The boosting mechanism reduces the weight of those training instances...

2009
Mehdi Khoury Honghai Liu

This research introduces and builds on the concept of Fuzzy Gaussian Inference(FGI) [1][2] as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone i...

2012

In this study, fuzzy rule-based classifier is used for the diagnosis of congenital heart disease. Congenital heart diseases are defined as structural or functional heart disease. Medical data sets were obtained from Pediatric Cardiology Department at Selcuk University, from years 2000 to 2003. Firstly, fuzzy rules were generated by using medical data. Then the weights of fuzzy rules were calcul...

2012
Ersin Kaya Bulent Oran

In this study, fuzzy rule-based classifier is used for the diagnosis of congenital heart disease. Congenital heart diseases are defined as structural or functional heart disease. Medical data sets were obtained from Pediatric Cardiology Department at Selcuk University, from years 2000 to 2003. Firstly, fuzzy rules were generated by using medical data. Then the weights of fuzzy rules were calcul...

2009
D. Devaraj

One of the important issues in the design of fuzzy classifier is the formation of fuzzy if-then rules and the membership functions. This paper presents a Genetic Algorithm (GA) approach to obtain the optimal rule set and the membership function. To develop the fuzzy system the membership functions and rule set are encoded into the chromosome and evolved simultaneously using Genetic Algorithm. A...

2012
Sunita Soni

In this paper we extend the problem of classification using Fuzzy Association Rule Mining and propose the concept of Fuzzy Weighted Associative Classifier (FWAC). Classification based on Association rules is considered to be effective and advantageous in many cases. Associative classifiers are especially fit to applications where the model may assist the domain experts in their decisions. Weigh...

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