- ``lambdarank``, `lambdarank <https://papers.nips.cc/paper/2971-learning-to-rank-with-nonsmooth-cost-functions.pdf>`__ objective. `label_gain <#label_gain>`__ can be used to set the gain (weight) of ``int`` label and all values in ``label`` must be smaller than number of elements in ``label_gain``
- ``rank_xendcg`` is faster than ``lambdarank`` and achieves the similar performance as ``lambdarank``
- ``rank_xendcg`` is faster than and achieves the similar performance as ``lambdarank``
- label should be ``int`` type, and larger number represents the higher relevance (e.g. 0:bad, 1:fair, 2:good, 3:perfect)
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@@ -805,9 +805,9 @@ Objective Parameters
- ``objective_seed`` :raw-html:`<a id="objective_seed" title="Permalink to this parameter" href="#objective_seed">🔗︎</a>`, default = ``5``, type = int
- random seed for objectives, if random process is needed
- used only in ``rank_xendcg`` objective
- used in ``rank_xendcg``
- random seed for objectives, if random process is needed
- ``num_class`` :raw-html:`<a id="num_class" title="Permalink to this parameter" href="#num_class">🔗︎</a>`, default = ``1``, type = int, aliases: ``num_classes``, constraints: ``num_class > 0``
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@@ -885,7 +885,7 @@ Objective Parameters
- used only in ``lambdarank`` application
- used for truncating the max_ndcg, refer to "truncation level" in the Sec.3 of `LambdaMART paper <https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR-TR-2010-82.pdf>`__ .
- used for truncating the max DCG, refer to "truncation level" in the Sec.3 of `LambdaMART paper <https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR-TR-2010-82.pdf>`__
- ``lambdarank_norm`` :raw-html:`<a id="lambdarank_norm" title="Permalink to this parameter" href="#lambdarank_norm">🔗︎</a>`, default = ``true``, type = bool
// descl2 = ``lambdarank``, `lambdarank <https://papers.nips.cc/paper/2971-learning-to-rank-with-nonsmooth-cost-functions.pdf>`__ objective. `label_gain <#label_gain>`__ can be used to set the gain (weight) of ``int`` label and all values in ``label`` must be smaller than number of elements in ``label_gain``
// descl2 = ``rank_xendcg`` is faster than and achieves the similar performance as ``lambdarank``
// descl2 = label should be ``int`` type, and larger number represents the higher relevance (e.g. 0:bad, 1:fair, 2:good, 3:perfect)
std::stringobjective="regression";
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@@ -706,8 +706,8 @@ struct Config {
#pragma region Objective Parameters
// desc = used only in ``rank_xendcg`` objective
// desc = random seed for objectives, if random process is needed
// desc = used in ``rank_xendcg``
intobjective_seed=5;
// check = >0
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@@ -768,7 +768,7 @@ struct Config {
// check = >0
// desc = used only in ``lambdarank`` application
// desc = used for truncating the max_ndcg, refer to "truncation level" in the Sec.3 of `LambdaMART paper <https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR-TR-2010-82.pdf>`__ .
// desc = used for truncating the max DCG, refer to "truncation level" in the Sec.3 of `LambdaMART paper <https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/MSR-TR-2010-82.pdf>`__