Rule-based classifier, that extract a subset of induced rules to efficiently learn/mine while preserving the discernibility information, plays crucial role in human-explainable artificial intelligence. However, this era big data, rule induction on whole datasets is computationally intensive. So far, best our knowledge, no known method focusing accelerating has been reported. This first study co...

An iterative method to select suitable features in an industrial fabric defect recognition context is proposed in this paper. It combines a global feature selection method based on the Choquet integral and a fuzzy linguistic rule classifier. The experimental study shows the wanted behaviour of this approach: the feature number decreases whereas the recognition rate increases. Thus, the number o...

In this work, we introduce a method for constructing capacities using overlap indexes between the fuzzy sets which are generated from the inputs of the considered problem. We also use these capacities to aggregate information by means of the Choquet integral in a fuzzy rule-based classifier. We observe that with these capacities the obtained results are better than those obtained with other mea...

The inductive learning of fuzzy rule-based classification systems usually encounters an issue of exponential growth of the fuzzy rulesearch space when the number of patternsand/or variables becomes large.This issue makes the learning process more difficultand, in most cases, may lead to scalability problems. Alcalá-Fdezet al.proposed a fuzzy association rule-based classification method for high...

This paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. Since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. These features are the occurrence probabilities of six exchange groups in the seque...

In the 3eld of fuzzy modelling, the exclusive consideration of the modelling error leads to problems concerning the handling of high-dimensional applications and the interpretability of the resulting rule base. To solve those problems, a statistically motivated fuzzy rule test is proposed. It decides if a fuzzy IF=THEN statement is a relevant rule or not. In this way, the problem of 3nding a go...

In this paper a new fuzzy method for 2D texture classification is proposed. A fuzzy rule base system is designed based on computed Geometric Moments (GMs), which are rotation, scale and translation invariant, for each texture class. Although GMs are applied to classify texture, utilizing fuzzy inference system (FIS) to make decision, develops much more robust classifier. Where GMs are inputs an...

Image processing techniques are bringing new insights to biomedical research. The automatic recognition and classification of biomedical objects can enhance work efficiency while identifying new inter-relationships among biological features. In this work, a simple rule-based decision tree classifier is developed to classify typical features of mixed cell types investigated by atomic force micro...

Water pressure tests are a common method of soil exploration in engineering geology. The classification of water pressure test results is usually carried out by expert geologists. This paper presents a method for the automatic classification of water pressure test curves. After discussing the features extracted from the test curves the fuzzy rule base used for classification is described. Some ...