Frédéric Ros

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In this paper, a hybrid genetic approach is proposed to solve the problem of designing a subdatabase of the original one with the highest classification performances, the lowest number of features and the highest number of patterns. The method can simultaneously treat the double problem of editing instance patterns and selecting features as a single(More)
Although genetic algorithms (GAs) have proved their ability to provide answers to the limitations of more conventional methods, they are comparatively inefficient in terms of the time needed to reach a repeatable solution of desired quality. An inappropriate selection of driving parameters is frequently blamed by practitioners. The use of hybrid schemes is(More)
This paper presents an objective and comparative study of evolutionary algorithms applied for designing two dimensional (2D) FIR filters. The design of 2-D FIR filters can be formulated as a non-linear optimization problem. We explore several stochastic methodologies capable of handling large spaces. We finally propose a new genetic algorithm where some(More)
In this paper, a new genetic algorithm is proposed for designing 2-D FIR filters with the objective of being relevant and tractable. The key point of our approach stems in the capacity of our GA to adapt the genetic operators during the genetic life while remaining simple and easy to implement. It hybridizes the use of conventional and dedicated processes.(More)
The design of finite impulse response (FIR) filters can be formulated as a non-linear optimization problem reputed to be difficult for conventional approaches. The constraints are high and a large number of parameters have to be estimated, especially when dealing with 2-D FIR filters. In order to improve the performance of conventional approaches, we(More)
A data set of 412 olfactory compounds, divided into animal, camphoraceous, ethereal and fatty olfaction classes, was submitted to an analysis by a Fuzzy Logic procedure called Adaptive Fuzzy Partition (AFP). This method aims to establish molecular descriptor/chemical activity relationships by dynamically dividing the descriptor space into a set of fuzzily(More)
This article studies the performance of two metaheuristics, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA), for FIR filter design. The two approaches aim to find a solution to a given objective function but employ different strategies and computational effort to do so. PSO is a more recent heuristic search method than GA; its dynamics exploit(More)
As clustering algorithms become more and more sophisticated to cope with current needs, large data sets of increasing complexity, sampling is likely to provide an interesting alternative. The proposal is a distance-based algorithm: The idea is to iteratively include in the sample the furthest item from all the already selected ones. Density is managed(More)
This paper investigates a method for instance selection in the context of supervised classification adapted to large databases. Based on the scale up concept, the method reduces the time required to perform the selection procedure by enabling the application of known condensation instance techniques to only small data sets instead of the whole set. The(More)