João Carlos Xavier

Learn More
One of the most important steps in the design of a multi-classifier system (MCS), also known as ensemble, is the choice of the components (classifiers). This step is very important to the overall performance of a MCS since the combination of a set of identical classifiers will not outperform the individual members. The ideal situation would be a set of(More)
The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant(More)
This paper presents a wide evaluation of performance and diversity in hybrid and non-hybrid structures of ensembles. In applying some diversity measures at the chosen ensemble, it is intended to analyse the effect of varying diversity in ensembles and how the variation of diversity can affect the performance of several combination methods (selection-based(More)
In this paper, we propose an automatic way of recommending information to be visualized by users. The list of information to be recommended is generated based on the web logs of the users stored by the system in a multi relational database. This system is a web-based multi-agent system which provides geographical information and monitors the actions of the(More)
Several clustering algorithms have been developed and applied to a great variety of problems in different fields. However, some of these algorithms have limitations. Bio-inspired algorithms have been applied to clustering problems aiming to overcome some of these limitations. In this paper, we apply the Coral Reefs Optimization (CRO) algorithm to clustering(More)
The main aim of biometric-based identification systems is to automatically recognize individuals based on their physiological and/or behavioural characteristics such as fingerprint, face, hand-geometry, among others. These systems offer several advantages over traditional forms of identity protection. However, there are still some important aspects that(More)
In a decision making process, we are usually oriented to take into consideration all the relevant features (characteristics) involved in a specific problem. In Machine Learning, for instance, a decision is made through the use of a learning algorithm and the characterization process is represented by the corresponding datasets. In this context,(More)
Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated world represents a complex system. Those simulations can however benefit from optimizations coming from the way in which agents react to changes in the simulated environment. This paper presents an approach for improving the efficiency of(More)