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Knowl. Discov. Data"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:p>In Wilkinson et al. [2011] we introduced a new set-covering random projection classifier that achieved average error lower than that of other classifiers in the Weka platform. This classifier was based on an<jats:italic>L<\/jats:italic><jats:sup>\u221e<\/jats:sup>norm distance function and exploited an iterative sequence of three stages (projecting, binning, and covering) to deal with the curse of dimensionality, computational complexity, and nonlinear separability. 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