Dávila Patrícia Ferreira Cruz

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The amount of data generated in different knowledge areas has made it necessary the use of data mining tools capable of automatically analyzing and extracting knowledge from datasets. Clustering is one of the most important tasks in data mining and can be defined as the process of partitioning objects into groups or clusters, such that objects in the same(More)
Different methods have been used to train radial basis function (RBF) neural networks. This paper proposes the use of a bee-inspired algorithm, named cOptBees, plus a heuristic to automatically select the number, location and dispersions of basis functions to be used in RBF networks. cOptBees was originally designed to solve data clustering problems and the(More)
Over the past two decades a wide range of nature-inspired clustering algorithms has been proposed in the literature with competitive performance when applied to solving real-world complex problems. One common feature of most of these algorithms is the need to set a number of internal parameters so that they can be suitably applied to these problems. These(More)
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