Tune and mix: learning to rank using ensembles of calibrated multi-class classifiers

In subset ranking , the goal is to learn a ranking function that approximates a gold standard partial ordering of a set of objects (in our case, a set of documents retrieved for the same query). The partial ordering is given by relevance labels representing the relevance of documents with respect to...

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