Leila M. Vriesmann

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This work evaluates some strategies to approximate the performance of a dynamic ensemble selection method to the oracle performance of its pool of weak classifiers. For this purpose, we evaluated different distance metrics in the K-nearest-oracles (KNORA) method, the use of statistics related to the class accuracy of each classifier in the pool and some(More)
This paper presents a k-nearest oracle-based dynamic ensemble selection method in which overall local accuracy (OLA) and local class accuracy (LCA) are combined into a twostep selection scheme. The OLA and LCA are computed on the neighborhood of the test pattern in a validation set to filter out the classifiers selected by the k-nearest oracles. The(More)
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