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The diversity of an ensemble of classifiers can be calculated in a variety of ways. Here a diversity metric and a means for altering the diversity of an ensemble, called ''thinning'', are introduced. We evaluate thinning algorithms created by several techniques on 22 publicly available datasets. When compared to other methods, our percentage correct diversity measure shows a greatest correlation between...
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