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Re-implement ROC-AUC. (#6747)

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* Re-implement ROC-AUC.

* Binary
* MultiClass
* LTR
* Add documents.

This PR resolves a few issues:
  - Define a value when the dataset is invalid, which can happen if there's an
  empty dataset, or when the dataset contains only positive or negative values.
  - Define ROC-AUC for multi-class classification.
  - Define weighted average value for distributed setting.
  - A correct implementation for learning to rank task.  Previous
  implementation is just binary classification with averaging across groups,
  which doesn't measure ordered learning to rank.
This commit is contained in:
Jiaming Yuan
2021-03-20 16:52:40 +08:00
committed by GitHub
parent 4ee8340e79
commit bcc0277338
27 changed files with 1622 additions and 461 deletions
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amalgamation/xgboost-all0.cc
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@@ -14,6 +14,7 @@
#include "../src/metric/elementwise_metric.cc"
#include "../src/metric/multiclass_metric.cc"
#include "../src/metric/rank_metric.cc"
#include "../src/metric/auc.cc"
#include "../src/metric/survival_metric.cc"
// objectives