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Ensemble pruning is crucial for the consideration of both predictive accuracy and predictive efficiency. Previous ensemble methods demand vast memory spaces and heavy computational burdens in dealing with large-scale datasets, which leads to the inefficiency for the problem of classification. To address the issue, this paper proposes a novel ensemble pruning algorithm based on the mining of frequent...
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