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From my read of the COBRA paper, the aggregation step is to train an inf-norm RadiusNeighborsRegressor over machine outputs and and y on the "l" data set. This should be more efficient than the existing linear scan through the "l" data. Am I misunderstanding the paper somehow?
The text was updated successfully, but these errors were encountered:
From my read of the COBRA paper, the aggregation step is to train an inf-norm RadiusNeighborsRegressor over machine outputs and and y on the "l" data set. This should be more efficient than the existing linear scan through the "l" data. Am I misunderstanding the paper somehow?
The text was updated successfully, but these errors were encountered: