This chapter is rooted in the ensemble framework and shows how order statistics can be used in the design of a "meta-learner" that examines the outputs of multiple distributed classifers and provides a final decision. Order statistics is one of the key tools of robust statistics, tailored to handling data with outliers. in a distributed data mining scenario in which there is wide variability among the individual classifers because of ...
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