Pairwise ranking objective implementation on gpu (#4873)
* - pairwise ranking objective implementation on gpu
- there are couple of more algorithms (ndcg and map) for which support will be added
as follow-up pr's
- with no label groups defined, get gradient is 90x faster on gpu (120m instance
mortgage dataset)
- it can perform by an order of magnitude faster with ~ 10 groups (and adequate cores
for the cpu implementation)
* Add JSON config to rank obj.
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tests/cpp/objective/test_ranking_obj_gpu.cu
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tests/cpp/objective/test_ranking_obj_gpu.cu
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#include "test_ranking_obj.cc"
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