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Glasgow, the only other UK city to have so far held the ECoC crown - in 1990 - also reaped the benefits.
Nevertheless, none of the presented techniques directly take into account the properties of the ECOC matrix.
In this paper, a novel Genetic strategy to optimize the ECOC coding step is presented.
Third, we present detailed performance evaluations of the ECOC algorithm running on mobile, resource-limited devices.
This paper situates the ECoC programme both within and beyond its marketing functions.
Ubeyli [11] provided another algorithm based on eigenvector methods and multiclass SVMs with the ECOC for the classification of EEG signals.
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The results show that the proposed method increases the classification accuracy in comparison with the state-of-the-art ECOC coding techniques.
However, most state-of-the-art ECOC approaches use a linear or exponential number of classifiers, making the discrimination of a large number of classes unfeasible.
The results over several UCI Machine Learning repository data sets and two real multi-class problems show that performance improvements can be obtained re-coding the classical one-versus-one and Sparse random designs compared to different state-of-the-art ECOC configurations.
With the extension of the binary ECOC to the ternary ECOC framework, ECOC designs have been proposed in order to better adapt to distributions of the data.
In this paper, we present a new formulation of the ternary ECOC distance and the error-correcting capabilities in the ternary ECOC framework.
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Justyna Jupowicz-Kozak
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