Add to ORKGThis paper presents Fuzzy-UCS, a Michigan-style Learn-ing Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS with the good interpretability of fuzzy rules to evolve highly accurate and understandable rulesets. Fuzzy-UCS is tested on a set of real-world problems, and compared to UCS and two of the most used machine learning techniques: C4.5 and SMO. The results show that Fuzzy-UCS is highly competitive to the three learners in terms of performance, and that the fuzzy representation permits a much better un-derstandability of the evolved knowledge. These promising results allow for further investigation on Fuzzy-UCS
The well-tried method of fuzzy classification is extended to hierarchical class structures to allow ...
Fuzzy classification, semi-supervised learning, data miningMagdeburg, Univ., Fak. für Informatik, Di...
AbstractIncremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that n...
Abstract. This paper introduces an approximate fuzzy representation to Fuzzy-UCS, a Michigan-style L...
The issue of rule generalization has received a great deal of attention in the discrete-valued learn...
We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of int...
The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning...
Abstract The extraction of models from data streams has become a hot topic in data mining due to the...
We present an experimental comparison between two approaches to optimization of the rules for a fuzz...
To design a fuzzy rule-based classi cation system (fuzzy classi er) with good generalization ability...
Decades ago, machine learning was not as good as human learning, so many machine learning techniques...
In a fuzzy classifier, the maping “inputs–output” is described by the linguistic 〈If–then〉 rules, th...
This report describes the fuzzy classifier system and a new payoff distribution scheme that performs...
[[abstract]]In real applications, data provided to a learning system usually contain linguistic info...
This paper addresses the issues in developing a fuzzy system for multiple classifier fusion. The pro...
The well-tried method of fuzzy classification is extended to hierarchical class structures to allow ...
Fuzzy classification, semi-supervised learning, data miningMagdeburg, Univ., Fak. für Informatik, Di...
AbstractIncremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that n...
Abstract. This paper introduces an approximate fuzzy representation to Fuzzy-UCS, a Michigan-style L...
The issue of rule generalization has received a great deal of attention in the discrete-valued learn...
We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of int...
The fuzzy classifier system (FCS) combines the ideas of fuzzy logic controllers (FLC's) and learning...
Abstract The extraction of models from data streams has become a hot topic in data mining due to the...
We present an experimental comparison between two approaches to optimization of the rules for a fuzz...
To design a fuzzy rule-based classi cation system (fuzzy classi er) with good generalization ability...
Decades ago, machine learning was not as good as human learning, so many machine learning techniques...
In a fuzzy classifier, the maping “inputs–output” is described by the linguistic 〈If–then〉 rules, th...
This report describes the fuzzy classifier system and a new payoff distribution scheme that performs...
[[abstract]]In real applications, data provided to a learning system usually contain linguistic info...
This paper addresses the issues in developing a fuzzy system for multiple classifier fusion. The pro...
The well-tried method of fuzzy classification is extended to hierarchical class structures to allow ...
Fuzzy classification, semi-supervised learning, data miningMagdeburg, Univ., Fak. für Informatik, Di...
AbstractIncremental algorithms for fuzzy classifiers are studied in this paper. It is assumed that n...