Add to ORKGSeveral issues arise when we consider building classifiers in general, and fuzzy classifiers in particular. These issues include but are not limited to attribute/feature selection, adoption of a specific approach/algorithm, evaluate the classifier performance, etc. We consider the opportunities that such classifiers have to offer and contrast them with the challenges they pose. © 2011 Springer-Verlag
Abstract: This paper describes the main ideas used in the development of a fuzzy classifier system w...
Fuzzy rule-based systems (FRBSs) are proficient in dealing with cognitive uncertainties like vaguene...
Abstract The extraction of models from data streams has become a hot topic in data mining due to the...
In a fuzzy classifier, the maping “inputs–output” is described by the linguistic 〈If–then〉 rules, th...
Abstract. Data mining means to summarize information from large amounts of raw data. It is one of th...
The issue of rule generalization has received a great deal of attention in the discrete-valued learn...
Dealing with classification problems in practice of-ten has to cope with uncertain information, ei-t...
When designing any type of fuzzy rule based system, considerable effort is placed in identifying the...
Since its inception, fuzzy logic has attracted an incredible amount of interest, and this interest c...
AbstractIncremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that n...
Fuzzy classification systems is defined in this paper as an aggregative model, in such a way that Ru...
Classes of real world datasets have various properties (such as imbalance, size, complexity, and cla...
This paper presents a general framework for designing a fuzzyrule-based classifier. Structure and pa...
This paper illustrated an evolutionary algorithm which learns classifiers, represented as sets of f...
We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of int...
Abstract: This paper describes the main ideas used in the development of a fuzzy classifier system w...
Fuzzy rule-based systems (FRBSs) are proficient in dealing with cognitive uncertainties like vaguene...
Abstract The extraction of models from data streams has become a hot topic in data mining due to the...
In a fuzzy classifier, the maping “inputs–output” is described by the linguistic 〈If–then〉 rules, th...
Abstract. Data mining means to summarize information from large amounts of raw data. It is one of th...
The issue of rule generalization has received a great deal of attention in the discrete-valued learn...
Dealing with classification problems in practice of-ten has to cope with uncertain information, ei-t...
When designing any type of fuzzy rule based system, considerable effort is placed in identifying the...
Since its inception, fuzzy logic has attracted an incredible amount of interest, and this interest c...
AbstractIncremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that n...
Fuzzy classification systems is defined in this paper as an aggregative model, in such a way that Ru...
Classes of real world datasets have various properties (such as imbalance, size, complexity, and cla...
This paper presents a general framework for designing a fuzzyrule-based classifier. Structure and pa...
This paper illustrated an evolutionary algorithm which learns classifiers, represented as sets of f...
We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of int...
Abstract: This paper describes the main ideas used in the development of a fuzzy classifier system w...
Fuzzy rule-based systems (FRBSs) are proficient in dealing with cognitive uncertainties like vaguene...
Abstract The extraction of models from data streams has become a hot topic in data mining due to the...