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While diversity has been argued to be the rationale for the success of an ensemble of classifiers, little has been said on how uniform use of the feature space influences classification error. Following an observation from a recent result, published elsewhere, among several ensembles of decision trees, those with a more uniform feature-use frequency also have a smaller classification error. This paper...
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