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To make the traditional support vector data description (SVDD) achieve better generalization performance and more robust against noise, a selective ensemble method based on correntropy and Renyi entropy is proposed. In this proposed ensemble method, the correntropy between the radii of the basis classifiers and the radius of the ensemble is utilized to substitute the sum-squared-error (SSE) criterion...
We investigate essential relationships between generalization capabilities and fuzziness of fuzzy classifiers (viz., the classifiers whose outputs are vectors of membership grades of a pattern to the individual classes). The study makes a claim and offers sound evidence behind the observation that higher fuzziness of a fuzzy classifier may imply better generalization aspects of the classifier, especially...
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