The clustering aims at assigning a set of objects to clusters in such a way that objects within the same cluster have a high degree of similarity, while objects belonging to different clusters are dissimilar. The clustering methods can be divided into hierarchical and nonhierarchical (partitioning) methods. In this paper, clustering by minimisation of a criterion function will be considered. Th...

Fuzzy logic and genetic algorithms are well-established computational techniques that have been employed to deal with the problem of classification as this is presented in the context of data mining. Based on Fuzzy Miner which is a recently proposed state-of-the-art fuzzy rule based system for numerical data, in this paper we propose GF-Miner which is a genetic fuzzy classifier that improves Fu...

Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membersh...

Based on the in-depth analysis of the essence and features of vague phenomena, this paper focuses on establishing the axiomatical foundation of membership degree theory for vague phenomena, presents an axiomatic system to govern membership degrees and their interconnections. On this basis, the concept of vague partition is introduced, further, the concept of fuzzy set introduced by Zadeh in 196...

In this paper we studied two different classifiers fusion algorithms exploiting the combination weights expressed over the entire data space and the combination with data dependent weights. The following aggregation schemes are employed in the study: the majority vote, the averaging, the combination via Choquet integral with the − λ fuzzy measure, the combination via space partitioning and clas...

The volume of energy loss that Brazilian electrical utilities have to deal with has been ever increasing. Electricity distribution companies have suffered significant and increasing losses in the last years, due to theft, measurement errors and other irregularities. Therefore there is a great concern to identify the profile of irregular customers, in order to reduce the volume of such losses. T...

In this work we describe a microdata protection method based on the use of fuzzy clustering and, more specifically, using fuzzy c-means. Microaggregation is a well-known masking method for microdata protection used by National Statistical Offices. Given a set of objects described in terms of a set of variables, this method consists on building a partition of the objects and then replace the ori...

We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning NFHBClass Method for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguist...