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...

In this paper an accurate real-time sequence-based system for representation, recognition and analysis of lowintensity facial expressions and FAUs is presented. The feature extraction is done using facial feature point tracking and biased discriminant analysis as an efficient dimension reduction method. A novel classification scheme based on neuro-fuzyy modeling of the FAU intensity is presente...

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...

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 ...

i n troduction: cancer is a major cause of mortality in the modern world, and one of the most important health problems in societies. during recent years, research on cancer as a system biology disease is focused on molecular differences between cancer cells and healthy cells. most of the proposed methods for classifying cancer using gene expression data act as black boxes and lack biological i...

The issue of finding fuzzy models with an interpretability as good as possible without decreasing the accuracy is one of the main research topics on genetic fuzzy systems. When they are used to perform on-line reinforcement learning by means of Michigan-style fuzzy classifier systems, this issue becomes even more difficult. Indeed, rule generalization (description of state-action relationships ...

We examine the performance of a fuzzy genetics-based machine learning method for multidimensional pattern classification problems with continuous attributes. In our method, each fuzzy if-then rule is handled as an individual, and a fitness value is assigned to each rule. Thus, our method can be viewed as a classifier system. In this paper, we first describe fuzzy if-then rules and fuzzy reasoni...